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- Updated dependencies in package.json for various packages including @ai-sdk/google-vertex, @ai-sdk/openai, framer-motion, motion, react-resizable-panels, and streamdown to their latest versions. - Added new workflows to the coding A2A Coordinator: - **safeRefactoringWorkflow**: Refactors code with E2B sandbox verification. - **testGenerationWorkflow**: Generates and runs tests for given code files. - **dataAnalysisWorkflow**: Conducts production-grade data analysis using coding agents and E2B sandboxes. - **automatedReportingWorkflow**: Gathers multi-section research and synthesizes it into a professional report. - Updated the codingTeamNetwork to include new workflows and improved documentation for agent delegation. - Enhanced the mastra index to include new workflows for better orchestration. - Improved logging and error handling across new workflows to ensure better traceability and debugging.
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Reviewer's GuideThis PR updates several AI/UX-related dependencies, formalizes project-wide coding guidelines, and introduces four new Mastra workflows (safe refactoring, test generation, data analysis, and automated reporting) wired into the coding A2A coordinator, coding team network, and Mastra index, with improved logging, error handling, and documentation for orchestration and delegation. Sequence diagram for dataAnalysisWorkflow execution with E2B sandboxsequenceDiagram
actor User
participant Mastra as MastraRoot
participant Coordinator as CodingA2ACoordinator
participant Workflow as DataAnalysisWorkflow
participant Step1 as GenerateAnalysisCodeStep
participant Architect as CodeArchitectAgent
participant Step2 as ExecuteAnalysisStep
participant E2BCreate as E2BCreateSandboxTool
participant E2BWrite as E2BWriteFileTool
participant E2BRun as E2BRunCodeTool
participant Step3 as GenerateDataReportStep
participant Reporter as ReportAgent
User->>Mastra: invoke dataAnalysisWorkflow(data, query, dataFormat, outputFormat)
Mastra->>Coordinator: route request (complex data analysis intent)
Coordinator->>Workflow: start(data, query, dataFormat, outputFormat)
%% Step 1: generate analysis code
Workflow->>Step1: execute(analysisInput)
Step1->>Architect: generate(prompt with data preview and query)
Architect-->>Step1: python analysis code
Step1-->>Workflow: code + data + query + dataFormat
%% Step 2: execute analysis in sandbox
Workflow->>Step2: execute(code, data, query, dataFormat)
Step2->>E2BCreate: execute(timeoutMS)
E2BCreate-->>Step2: sandboxId
Step2->>E2BWrite: execute(sandboxId, data.ext, content)
E2BWrite-->>Step2: ok
Step2->>E2BRun: execute(sandboxId, code, language=python)
E2BRun-->>Step2: execution logs(stdout, stderr)
Step2-->>Workflow: stdout, stderr, plotGenerated, query
%% Step 3: synthesize report
Workflow->>Step3: execute(stdout, stderr, plotGenerated, query)
Step3->>Reporter: generate(prompt with logs and errors)
Reporter-->>Step3: JSON(report, insights)
Step3-->>Workflow: report, insights, artifacts
Workflow-->>Coordinator: analysisOutput(report, insights, artifacts)
Coordinator-->>Mastra: response
Mastra-->>User: final analysis report
Sequence diagram for safeRefactoringWorkflow with sandbox verificationsequenceDiagram
actor User
participant Mastra as MastraRoot
participant Coordinator as CodingA2ACoordinator
participant Workflow as SafeRefactoringWorkflow
participant Step1 as GenerateRefactorStep
participant RefactorAgent as RefactoringAgent
participant Step2 as VerifyRefactorStep
participant E2BCreate as E2BCreateSandboxTool
participant E2BWrite as E2BWriteFileTool
participant E2BRunCmd as E2BRunCommandTool
User->>Mastra: invoke safeRefactoringWorkflow(sourceCode, filePath, goal, language)
Mastra->>Coordinator: route request (refactor intent)
Coordinator->>Workflow: start(refactorInput)
%% Step 1: generate refactored code
Workflow->>Step1: execute(refactorInput)
Step1->>RefactorAgent: generate(prompt with code and goal)
RefactorAgent-->>Step1: object(refactoredCode, explanation)
Step1-->>Workflow: sourceCode, filePath, language, goal, refactoredCode, explanation
%% Step 2: verify in sandbox
Workflow->>Step2: execute(refactorState)
Step2->>E2BCreate: execute(timeoutMS)
E2BCreate-->>Step2: sandboxId
Step2->>E2BWrite: execute(sandboxId, filePath, refactoredCode)
E2BWrite-->>Step2: ok
Step2->>E2BRunCmd: execute(sandboxId, checkCommand, timeoutMs, captureOutput)
E2BRunCmd-->>Step2: success, stdout, stderr
Step2-->>Workflow: refactoredCode, explanation, verificationResult
Workflow-->>Coordinator: refactorOutput(refactoredCode, explanation, verificationResult)
Coordinator-->>Mastra: response
Mastra-->>User: verified refactored code + verification summary
Class diagram for new Mastra workflows and their collaboratorsclassDiagram
class DataAnalysisWorkflow {
+analysisInputSchema
+analysisOutputSchema
+generateAnalysisCodeStep
+executeAnalysisStep
+generateDataReportStep
+commit()
}
class SafeRefactoringWorkflow {
+refactorInputSchema
+refactorOutputSchema
+generateRefactorStep
+verifyRefactorStep
+commit()
}
class AutomatedReportingWorkflow {
+reportInputSchema
+reportOutputSchema
+researchTopicStep
+synthesizeReportStep
+commit()
}
class GenerateAnalysisCodeStep {
+id
+description
+execute()
}
class ExecuteAnalysisStep {
+id
+description
+execute()
}
class GenerateDataReportStep {
+id
+description
+execute()
}
class GenerateRefactorStep {
+id
+description
+execute()
}
class VerifyRefactorStep {
+id
+description
+execute()
}
class ResearchTopicStep {
+id
+description
+execute()
}
class SynthesizeReportStep {
+id
+description
+execute()
}
class CodeArchitectAgent {
+generate(prompt)
}
class ReportAgent {
+generate(prompt)
}
class ResearchAgent {
+generate(prompt)
}
class RefactoringAgent {
+generate(prompt)
}
class E2BCreateSandboxTool {
+execute(timeoutMS)
}
class E2BRunCodeTool {
+execute(sandboxId, code, language)
}
class E2BWriteFileTool {
+execute(sandboxId, path, content)
}
class E2BRunCommandTool {
+execute(sandboxId, command, timeoutMs, captureOutput)
}
class CodingA2ACoordinator {
+researchSynthesisWorkflow
+specGenerationWorkflow
+repoIngestionWorkflow
+learningExtractionWorkflow
+financialReportWorkflow
+safeRefactoringWorkflow
+testGenerationWorkflow
+dataAnalysisWorkflow
+automatedReportingWorkflow
}
class MastraRoot {
+workflows
+agents
}
%% Workflow composition
DataAnalysisWorkflow *-- GenerateAnalysisCodeStep
DataAnalysisWorkflow *-- ExecuteAnalysisStep
DataAnalysisWorkflow *-- GenerateDataReportStep
SafeRefactoringWorkflow *-- GenerateRefactorStep
SafeRefactoringWorkflow *-- VerifyRefactorStep
AutomatedReportingWorkflow *-- ResearchTopicStep
AutomatedReportingWorkflow *-- SynthesizeReportStep
%% Step dependencies on agents
GenerateAnalysisCodeStep ..> CodeArchitectAgent
GenerateDataReportStep ..> ReportAgent
ResearchTopicStep ..> ResearchAgent
SynthesizeReportStep ..> ReportAgent
GenerateRefactorStep ..> RefactoringAgent
%% Step dependencies on E2B tools
ExecuteAnalysisStep ..> E2BCreateSandboxTool
ExecuteAnalysisStep ..> E2BWriteFileTool
ExecuteAnalysisStep ..> E2BRunCodeTool
VerifyRefactorStep ..> E2BCreateSandboxTool
VerifyRefactorStep ..> E2BWriteFileTool
VerifyRefactorStep ..> E2BRunCommandTool
%% Registration and orchestration
MastraRoot o-- DataAnalysisWorkflow
MastraRoot o-- SafeRefactoringWorkflow
MastraRoot o-- AutomatedReportingWorkflow
CodingA2ACoordinator o-- DataAnalysisWorkflow
CodingA2ACoordinator o-- SafeRefactoringWorkflow
CodingA2ACoordinator o-- AutomatedReportingWorkflow
File-Level Changes
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Summary by CodeRabbit
✏️ Tip: You can customize this high-level summary in your review settings. WalkthroughThis PR adds four new AI workflows to the Mastra framework (data analysis, automated reporting, safe refactoring, test generation), registers them in the coordinator and network, updates the mastra instance configuration, bumps dependency versions, and comprehensively revamps AGENTS.md documentation with standardized coding guidelines and command references. Changes
Estimated code review effort🎯 4 (Complex) | ⏱️ ~45 minutes Possibly related PRs
Suggested reviewers
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Pre-merge checks and finishing touches✅ Passed checks (3 passed)
✨ Finishing touches
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Summary of ChangesHello @ssdeanx, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request significantly enhances the system's AI capabilities and developer experience. It updates several key dependencies to their latest versions, ensuring the project remains current and stable. More importantly, it introduces a suite of powerful new AI workflows designed to automate complex software development tasks such as safe code refactoring, test generation, data analysis, and automated reporting. These new workflows are seamlessly integrated into the existing agent coordination mechanisms, alongside comprehensive updates to documentation and code style guidelines, providing clearer development standards and improving overall system orchestration. Highlights
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Hey - I've found 3 issues, and left some high level feedback:
- Several workflows (e.g.,
dataAnalysisWorkflow,testGenerationWorkflow,automatedReportingWorkflow) parseresult.textas JSON without validation or fallback when the model returns non‑JSON or JSON-with-markdown; consider standardizing on structured outputs (result.objector a zod schema) or adding robust parsing/validation with clear error messaging. - The E2B sandbox commands in the refactoring and test-generation workflows (e.g.,
npx -y typescript tsc,npx -y vitest,pip install pytest) are tightly coupled to specific tooling and may be slow or flaky; consider centralizing these command templates/configuration and short-circuiting when the language or environment isn't supported to make failures more predictable. - The new coordinator/network instruction blocks are quite detailed but still only describe a subset of the newly added workflows (e.g., data analysis and automated reporting); it may help downstream orchestration if their triggers, expected inputs, and ideal usage patterns are documented in the same registry-style format as the existing workflows.
Prompt for AI Agents
Please address the comments from this code review:
## Overall Comments
- Several workflows (e.g., `dataAnalysisWorkflow`, `testGenerationWorkflow`, `automatedReportingWorkflow`) parse `result.text` as JSON without validation or fallback when the model returns non‑JSON or JSON-with-markdown; consider standardizing on structured outputs (`result.object` or a zod schema) or adding robust parsing/validation with clear error messaging.
- The E2B sandbox commands in the refactoring and test-generation workflows (e.g., `npx -y typescript tsc`, `npx -y vitest`, `pip install pytest`) are tightly coupled to specific tooling and may be slow or flaky; consider centralizing these command templates/configuration and short-circuiting when the language or environment isn't supported to make failures more predictable.
- The new coordinator/network instruction blocks are quite detailed but still only describe a subset of the newly added workflows (e.g., data analysis and automated reporting); it may help downstream orchestration if their triggers, expected inputs, and ideal usage patterns are documented in the same registry-style format as the existing workflows.
## Individual Comments
### Comment 1
<location> `src/mastra/workflows/data-analysis-workflow.ts:244-245` </location>
<code_context>
+ `;
+
+ try {
+ const result = await reportAgent.generate(prompt);
+
+ let output;
</code_context>
<issue_to_address>
**issue (bug_risk):** Parsing the LLM response as JSON without validation is brittle and may cause runtime failures.
This relies on `reportAgent.generate` always returning valid JSON in `result.text`; any extra prose, code fences, or minor formatting issues will cause `JSON.parse` to throw and break the workflow. Consider using a structured/object output mode for `reportAgent` or validating/parsing via a zod schema with a fallback (as in `automatedReportingWorkflow`) to make this step more resilient to imperfect model outputs.
</issue_to_address>
### Comment 2
<location> `src/mastra/workflows/safe-refactoring-workflow.ts:125-129` </location>
<code_context>
+ const span = tracer.startSpan('e2b-analysis-execution');
+
+ try {
+ const sandbox = await createSandbox.execute({
+ timeoutMS: 300_000,
+ }, { mastra, requestContext });
</code_context>
<issue_to_address>
**issue (bug_risk):** Using `instanceof z.ZodError` on the `createSandbox.execute` result is likely incorrect and may hide real failures.
Since E2B tools throw on validation errors rather than returning `ZodError` instances, this `sandbox instanceof z.ZodError` branch will effectively never run, and the subsequent cast to `{ sandboxId: string }` may allow an invalid value through. Instead, rely on exceptions with try/catch, or explicitly validate the shape (e.g. `if (!('sandboxId' in sandbox))`) and fail fast with a clear error.
</issue_to_address>
### Comment 3
<location> `src/mastra/workflows/data-analysis-workflow.ts:205` </location>
<code_context>
+ plotGenerated: z.boolean(),
+ query: z.string(),
+ }),
+ outputSchema: analysisOutputSchema,
+ execute: async ({ inputData, writer }) => {
+ const startTime = Date.now();
</code_context>
<issue_to_address>
**nitpick:** `outputFormat` is accepted in the input schema but never influences the workflow output.
Since `analysisInputSchema` exposes an `outputFormat` enum (`markdown | pdf | html`) but the workflow always returns a markdown `report` and never checks this field, the option is currently misleading. Either remove `outputFormat` from the schema until multiple formats are supported, or pass it through to `generateDataReportStep` and implement branching/format-specific handling so the parameter has an effect.
</issue_to_address>Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.
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Code Review
This pull request introduces several valuable new workflows for refactoring, test generation, data analysis, and reporting, along with significant documentation improvements that enhance clarity for developers. The dependency updates are also noted. My review focuses on improving the robustness, performance, and consistency of the new workflows. Key suggestions include parallelizing sequential operations for better performance, adding robust error handling for JSON parsing to prevent workflow failures, and improving type safety by replacing unsafe assertions with type guards.
| const researchedSections = []; | ||
|
|
||
| for (const section of inputData.sections) { | ||
| await writer?.custom({ | ||
| type: 'data-tool-progress', | ||
| data: { | ||
| status: 'in-progress', | ||
| message: `Researching section: ${section}...`, | ||
| stage: 'research-topic', | ||
| }, | ||
| id: 'research-topic', | ||
| }); | ||
|
|
||
| const prompt = `Research the following aspect of "${inputData.topic}": ${section}. | ||
| Provide a ${inputData.depth} summary of key facts, trends, and data points.`; | ||
|
|
||
| const result = await researchAgent.generate(prompt); | ||
| researchedSections.push({ | ||
| name: section, | ||
| data: result.text, | ||
| }); | ||
| } |
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The research for each section is performed sequentially in a for...of loop. Since these research tasks are independent, they can be executed in parallel using Promise.all. This will significantly improve the performance of the researchTopicStep, especially for reports with many sections.
const researchPromises = inputData.sections.map(async (section) => {
await writer?.custom({
type: 'data-tool-progress',
data: {
status: 'in-progress',
message: `Researching section: ${section}...`,
stage: 'research-topic',
},
id: 'research-topic',
});
const prompt = `Research the following aspect of "${inputData.topic}": ${section}.
Provide a ${inputData.depth} summary of key facts, trends, and data points.`
const result = await researchAgent.generate(prompt);
return {
name: section,
data: result.text,
};
});
const researchedSections = await Promise.all(researchPromises);| const output = JSON.parse(result.text); | ||
|
|
||
| await writer?.custom({ | ||
| type: 'data-tool-progress', | ||
| data: { | ||
| status: 'done', | ||
| message: `Report generated successfully.`, | ||
| stage: 'generate-data-report', | ||
| }, | ||
| id: 'generate-data-report', | ||
| }); | ||
|
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| logStepEnd('generate-data-report', {}, Date.now() - startTime); | ||
|
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||
| return { | ||
| report: output.report, | ||
| insights: output.insights, | ||
| artifacts: inputData.plotGenerated ? [{ name: 'plot.png', type: 'image/png' }] : [], | ||
| }; |
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The call to JSON.parse(result.text) can throw an error if the LLM returns invalid JSON, which would cause the entire workflow to fail. For improved robustness, consider wrapping this in its own try...catch block and providing a fallback object, similar to the pattern used in automated-reporting-workflow.ts.
let output;
try {
output = JSON.parse(result.text);
} catch {
output = {
report: `Analysis Results:\n\n${inputData.stdout}`,
insights: ["Could not parse structured insights from model output."],
};
}
await writer?.custom({
type: 'data-tool-progress',
data: {
status: 'done',
message: `Report generated successfully.`,
stage: 'generate-data-report',
},
id: 'generate-data-report',
});
logStepEnd('generate-data-report', {}, Date.now() - startTime);
return {
report: output.report,
insights: output.insights,
artifacts: inputData.plotGenerated ? [{ name: 'plot.png', type: 'image/png' }] : [],
};| if (sandbox instanceof z.ZodError) { | ||
| throw new Error(sandbox.message); | ||
| } | ||
|
|
||
| const { sandboxId } = sandbox as { sandboxId: string }; |
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The code uses instanceof z.ZodError for error checking and then an unsafe type assertion sandbox as { sandboxId: string }. This is risky and inconsistent with other parts of the codebase that use a type guard like if ('error' in sandbox). Please use a type guard to safely access sandboxId and improve type safety.
| if (sandbox instanceof z.ZodError) { | |
| throw new Error(sandbox.message); | |
| } | |
| const { sandboxId } = sandbox as { sandboxId: string }; | |
| if (!sandbox || !('sandboxId' in sandbox)) { | |
| throw new Error('Failed to create sandbox or sandboxId is missing.'); | |
| } | |
| const { sandboxId } = sandbox; |
| const parsed = JSON.parse(result.text); | ||
| const output = parsed ?? { | ||
| testCode: '', | ||
| testFilePath | ||
| }; |
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The call to JSON.parse(result.text) can throw an error if the LLM returns malformed JSON, causing the workflow to fail. To make the workflow more robust, you should wrap this in a try...catch block and provide a fallback, similar to the pattern in generateRefactorStep in safe-refactoring-workflow.ts.
let output;
try {
const parsed = JSON.parse(result.text);
output = parsed ?? { testCode: '', testFilePath };
} catch {
output = {
testCode: `// Failed to parse test code from model.`,
testFilePath,
};
}| param: z.string().describe('Parameter description'), | ||
| }), | ||
| outputSchema: z.object({ | ||
| data: z.any(), |
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The Tool Implementation Pattern example uses z.any() for the data field in outputSchema. This contradicts the "TypeScript Conventions" section (line 143) which states "No any: Use unknown or proper types". To maintain consistency and promote best practices within the documentation, please use a more specific type or z.unknown().
| data: z.any(), | |
| data: z.unknown(), |
| // Tool logic here | ||
| log.info('Tool executed', { context }) | ||
|
|
||
| return { data: result, error: undefined } |
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In the Tool Implementation Pattern example, the result variable is used in the return statement but is never defined within the try block. This could be confusing for developers following the pattern and makes the example code invalid. Please add a placeholder definition for result to make the example complete.
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Pull request overview
This PR enhances the Mastra coding platform by adding four new automated workflows for code quality and analysis, while keeping dependencies up-to-date with minor version bumps.
- Introduces production-grade workflows for safe refactoring, test generation, data analysis, and automated reporting
- Updates 7 AI SDK and UI library dependencies to their latest patch versions
- Integrates new workflows into the codingA2ACoordinator and main Mastra instance
- Improves codingTeamNetwork documentation with more structured agent registry and workflow invocation patterns
Reviewed changes
Copilot reviewed 10 out of 11 changed files in this pull request and generated 14 comments.
Show a summary per file
| File | Description |
|---|---|
| src/mastra/workflows/test-generation-workflow.ts | Adds workflow to generate unit tests using testEngineerAgent and verify them in E2B sandbox |
| src/mastra/workflows/safe-refactoring-workflow.ts | Adds workflow to refactor code with syntax verification in E2B sandbox |
| src/mastra/workflows/data-analysis-workflow.ts | Adds workflow for Python-based data analysis with E2B execution and report generation |
| src/mastra/workflows/automated-reporting-workflow.ts | Adds workflow to research multiple sections and synthesize into professional reports |
| src/mastra/workflows/index.ts | Exports the four new workflows for public use |
| src/mastra/a2a/codingA2ACoordinator.ts | Registers new workflows and updates coordinator instructions |
| src/mastra/index.ts | Registers dataAnalysisWorkflow and automatedReportingWorkflow in Mastra instance |
| src/mastra/networks/codingTeamNetwork.ts | Restructures documentation with clearer agent registry and operational logic |
| package.json | Updates @AI-SDK packages, framer-motion, motion, react-resizable-panels, and streamdown |
| package-lock.json | Reflects dependency version updates with new package resolutions |
| AGENTS.md | Adds comprehensive code style guidelines, testing standards, and tool/agent implementation patterns |
| const parsed = JSON.parse(result.text); | ||
| const output = parsed ?? { | ||
| testCode: '', | ||
| testFilePath |
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Inconsistent error handling pattern compared to safe-refactoring-workflow. In safe-refactoring-workflow line 68, the result uses result.object, but here it uses JSON.parse(result.text). If testEngineerAgent returns structured output similar to refactoringAgent, this should use result.object for consistency. If the agents return different formats, this inconsistency should be documented or standardized.
| const parsed = JSON.parse(result.text); | |
| const output = parsed ?? { | |
| testCode: '', | |
| testFilePath | |
| // Prefer structured object output when available, for consistency with other workflows. | |
| let output: { testCode: string; testFilePath?: string } | null | undefined = | |
| // @ts-expect-error: result.object shape is provided by the agent at runtime. | |
| (result as any).object; | |
| if (!output) { | |
| try { | |
| output = JSON.parse(result.text); | |
| } catch (parseError) { | |
| // Log parse errors and fall back to a minimal default. | |
| logError('generate-tests-parse', parseError); | |
| output = { | |
| testCode: '', | |
| testFilePath, | |
| }; | |
| } | |
| } | |
| output = output ?? { | |
| testCode: '', | |
| testFilePath, |
| if (sandbox instanceof z.ZodError) { | ||
| throw new Error(sandbox.message); | ||
| } |
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Inconsistent error handling pattern: checking sandbox instanceof z.ZodError but then checking execution instanceof z.ZodError later. This is inconsistent with test-generation-workflow which uses 'error' in sandbox pattern. The codebase should standardize on one error handling pattern across all workflows for maintainability.
| if (!('sandboxId' in sandbox)) { | ||
| throw new Error('Failed to create sandbox'); | ||
| } | ||
|
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| const { sandboxId } = sandbox; | ||
|
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| // Write data file | ||
| await writeFile.execute({ | ||
| sandboxId, | ||
| path: `data.${inputData.dataFormat}`, | ||
| content: inputData.data, | ||
| }, { mastra, requestContext }); | ||
|
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| // Run code | ||
| const executionResult = await runCode.execute({ | ||
| sandboxId, | ||
| code: inputData.code, | ||
| runCodeOpts: { | ||
| language: 'python', | ||
| }, | ||
| }, { mastra, requestContext }); | ||
|
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| if (!('execution' in executionResult)) { | ||
| throw new Error('Failed to execute code'); | ||
| } |
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Inconsistent error checking pattern. Lines 135 and 157 check for 'sandboxId' in sandbox and 'execution' in executionResult, but this is different from the test-generation-workflow which checks for 'error' in sandbox. These different patterns make the codebase harder to maintain. Consider standardizing error handling across all workflows.
| stdout: execution.logs.stdout.join('\n'), | ||
| stderr: execution.logs.stderr.join('\n'), |
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Unsafe property access. The code assumes execution.logs.stdout and execution.logs.stderr are arrays without validation after JSON parsing. If the structure differs, this will cause a runtime error. Consider validating the parsed object structure or using optional chaining with fallbacks: execution.logs?.stdout?.join('\n') ?? ''.
| // Actually, let's try to run it or just check syntax. | ||
| // Simple syntax check: tsc --noEmit | ||
| // We need to write a package.json or assume global tsc | ||
| checkCommand = `npx -y typescript tsc ${inputData.filePath} --noEmit --target esnext --module commonjs`; |
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The comment describes installing typescript if not present and mentions needing a package.json, but the command uses npx -y typescript tsc which is incorrect. The correct command should be npx -y tsc since 'typescript' is the package name and 'tsc' is the binary. Using npx -y typescript tsc would try to run a package called 'typescript' with 'tsc' as an argument, which will fail.
| checkCommand = `npx -y typescript tsc ${inputData.filePath} --noEmit --target esnext --module commonjs`; | |
| checkCommand = `npx -y tsc ${inputData.filePath} --noEmit --target esnext --module commonjs`; |
| const execResult = execution as { | ||
| success: boolean; | ||
| exitCode: number; | ||
| stdout: string; | ||
| stderr: string; | ||
| command: string; | ||
| executionTime: number; | ||
| error?: undefined; | ||
| }; | ||
|
|
There was a problem hiding this comment.
Another unsafe type assertion. Similar to the sandbox issue, after checking for ZodError, the code uses as { success: boolean; ... } without validating the execution object structure. This could lead to accessing undefined properties at runtime if the object doesn't match the expected shape.
| const execResult = execution as { | |
| success: boolean; | |
| exitCode: number; | |
| stdout: string; | |
| stderr: string; | |
| command: string; | |
| executionTime: number; | |
| error?: undefined; | |
| }; | |
| const executionResultSchema = z.object({ | |
| success: z.boolean(), | |
| exitCode: z.number(), | |
| stdout: z.string(), | |
| stderr: z.string(), | |
| command: z.string(), | |
| executionTime: z.number(), | |
| error: z.undefined().optional(), | |
| }); | |
| const parsedExecutionResult = executionResultSchema.safeParse(execution); | |
| if (!parsedExecutionResult.success) { | |
| throw new Error( | |
| `Invalid execution result structure: ${parsedExecutionResult.error.message}`, | |
| ); | |
| } | |
| const execResult = parsedExecutionResult.data; |
|
|
||
| try { | ||
| const result = await reportAgent.generate(prompt); | ||
| const output = JSON.parse(result.text); |
There was a problem hiding this comment.
Missing error handling for JSON.parse. If the agent returns invalid JSON in result.text, this will throw an unhandled exception. Consider wrapping in a try-catch block or using a safer parsing approach with validation, similar to the automated-reporting-workflow which has a try-catch around JSON.parse (lines 145-153).
| const output = JSON.parse(result.text); | |
| let output; | |
| try { | |
| output = JSON.parse(result.text); | |
| } catch (parseError) { | |
| const parsingMessage = | |
| parseError instanceof Error ? parseError.message : String(parseError); | |
| const errorWithContext = new Error( | |
| `Failed to parse reportAgent response as JSON in generate-data-report step: ${parsingMessage}`, | |
| ); | |
| logError('generate-data-report', errorWithContext); | |
| throw errorWithContext; | |
| } |
| throw new Error('Failed to execute code'); | ||
| } | ||
|
|
||
| const execution = JSON.parse(executionResult.execution); |
There was a problem hiding this comment.
Missing error handling for JSON.parse. If executionResult.execution contains invalid JSON, this will throw an unhandled exception that bypasses the try-catch block's intended error handling. Wrap this in a try-catch or validate the JSON structure before parsing.
| const execution = JSON.parse(executionResult.execution); | |
| let execution; | |
| try { | |
| execution = JSON.parse(executionResult.execution); | |
| } catch (error) { | |
| logError?.('Failed to parse execution result as JSON', error); | |
| span.setStatus({ code: SpanStatusCode.ERROR, message: 'Failed to parse execution result as JSON' }); | |
| span.end(); | |
| throw new Error('Invalid execution result format'); | |
| } |
| // Check if plot was generated (simple check via stdout or just assume if code was meant to) | ||
| // In a real production scenario, we'd check if 'plot.png' exists using listFiles | ||
| const plotGenerated = inputData.code.includes('plot.png'); |
There was a problem hiding this comment.
The comment on line 163 states "Check if plot was generated (simple check via stdout or just assume if code was meant to)" but the actual implementation only checks if the string 'plot.png' exists in the code, not whether the file was actually created. This could lead to incorrect plotGenerated values. The comment suggests checking via listFiles for a production scenario, which would be more accurate.
| // Check if plot was generated (simple check via stdout or just assume if code was meant to) | |
| // In a real production scenario, we'd check if 'plot.png' exists using listFiles | |
| const plotGenerated = inputData.code.includes('plot.png'); | |
| // Check if plot was generated (simple check via stdout or, as a fallback, assume if code was meant to) | |
| // In a real production scenario, we'd check if 'plot.png' exists using listFiles | |
| const stdoutText = | |
| execution?.logs?.stdout && Array.isArray(execution.logs.stdout) | |
| ? execution.logs.stdout.join('\n') | |
| : String(execution?.logs?.stdout ?? ''); | |
| const plotGenerated = stdoutText.includes('plot.png') || inputData.code.includes('plot.png'); |
| Framework: ${inputData.language === 'python' ? 'pytest' : 'vitest'} | ||
|
|
||
| Code: | ||
| \`\`${inputData.language} |
There was a problem hiding this comment.
The prompt template uses incomplete markdown code fences. Line 58 shows \`${inputData.language}` which will produce incorrect markdown rendering. This should be three backticks to properly format the code block.
| \`\`${inputData.language} | |
| \`\`\`${inputData.language} |
![coderabbitai[bot]](https://avatars.githubusercontent.com/in/347564?s=60&v=4){kind=small}
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Actionable comments posted: 18
Caution
Some comments are outside the diff and can’t be posted inline due to platform limitations.
⚠️ Outside diff range comments (1)
AGENTS.md (1)
7-7: Consider breaking long lines for better readability.Several lines exceed the 80-character limit recommended in the markdown coding guidelines. While the content is readable, breaking these lines would improve maintainability.
Example for line 7:
-Mastra is a production-grade multi-agent framework for building agent-driven applications and RAG (retrieval-augmented generation) workflows. It provides **60+ enterprise tools**, **31+ specialized agents**, **15+ workflows**, **13 agent networks**, **A2A/MCP orchestration**, and a **complete UI component library** (65 components: 30 AI Elements + 35 base UI) for scalable AI systems. Key capabilities include **financial intelligence**, **RAG pipelines**, **observability**, **secure governance**, and **AI chat interfaces**. +Mastra is a production-grade multi-agent framework for building +agent-driven applications and RAG (retrieval-augmented generation) +workflows. It provides **60+ enterprise tools**, **31+ specialized +agents**, **15+ workflows**, **13 agent networks**, **A2A/MCP +orchestration**, and a **complete UI component library** (65 +components: 30 AI Elements + 35 base UI) for scalable AI systems. +Key capabilities include **financial intelligence**, **RAG pipelines**, +**observability**, **secure governance**, and **AI chat interfaces**.As per coding guidelines, markdown line length should be limited to 80 characters for readability.
Also applies to: 296-300
🤖 Fix all issues with AI Agents
In @src/mastra/a2a/codingA2ACoordinator.ts:
- Around line 162-171: The documentation block listing high-level workflows is
missing descriptions for dataAnalysisWorkflow and automatedReportingWorkflow;
update the comment where the workflows are described (the block that currently
lists researchSynthesisWorkflow, specGenerationWorkflow, repoIngestionWorkflow,
learningExtractionWorkflow, financialReportWorkflow, safeRefactoringWorkflow,
testGenerationWorkflow) to include concise descriptions for dataAnalysisWorkflow
and automatedReportingWorkflow so the comment matches the actual registered
workflows in the workflows object and eliminates the inconsistency.
In @src/mastra/networks/codingTeamNetwork.ts:
- Around line 60-66: The HIGH-LEVEL WORKFLOW REGISTRY in codingTeamNetwork is
missing the four workflows (safeRefactoringWorkflow, testGenerationWorkflow,
dataAnalysisWorkflow, automatedReportingWorkflow) that are imported and used in
codingA2ACoordinator; update codingTeamNetwork to either (A) import those four
symbols and add them to the registry text block and to the exported workflows
object (the "workflows" variable) so routing supports them, or (B) if omission
is intentional, add a concise comment above the registry explaining the
architectural separation between codingTeamNetwork (routing) and
codingA2ACoordinator (parallel orchestration) and why these workflows are only
registered there. Ensure references to the symbols safeRefactoringWorkflow,
testGenerationWorkflow, dataAnalysisWorkflow, automatedReportingWorkflow,
codingA2ACoordinator, and the workflows object are consistent.
In @src/mastra/workflows/automated-reporting-workflow.ts:
- Around line 7-23: The local reportOutputSchema in
automated-reporting-workflow.ts duplicates the name of an existing
reportOutputSchema in src/mastra/config/agent-schemas.ts; rename or reuse it to
avoid confusion. Either rename the local symbol (e.g.,
automatedReportOutputSchema) and update any references in this file
(reportOutputSchema -> automatedReportOutputSchema), or import and extend the
shared reportOutputSchema from agent-schemas.ts (use extension/merge logic and
update references) so there aren’t two different exports with the same name.
- Around line 29-36: The outputSchema currently types depth as z.string() which
mismatches the inputSchema's depth defined as
z.enum(['brief','detailed','comprehensive']); update outputSchema to use the
same enum (e.g., replace depth: z.string() with depth:
z.enum(['brief','detailed','comprehensive']) or reuse a shared constant/variable
for the enum) so both inputSchema and outputSchema enforce identical allowed
depth values; ensure you reference the same symbol (the enum or sharedDepth
constant) to avoid duplication.
In @src/mastra/workflows/data-analysis-workflow.ts:
- Around line 163-165: The current plot detection uses a string check on
inputData.code (plotGenerated = inputData.code.includes('plot.png')), which is
unreliable; replace this with an actual file existence check by calling the
async listFiles API and verifying the presence of 'plot.png' (or other expected
output names). Update the code that sets plotGenerated to await listFiles(),
inspect the returned filenames (e.g., files.includes('plot.png') or any file
matching a pattern like /\.png$/), handle errors and the async context (make the
surrounding function async if needed), and fall back to false if the call fails
or no matching files are found.
- Around line 243-266: The try block that calls reportAgent.generate(prompt) and
immediately JSON.parse(result.text) can crash if the LLM returns malformed JSON;
update the catch/fallback logic in the generate-data-report step to handle JSON
parsing failures: attempt to parse result.text and if JSON.parse throws,
fallback to treating result.text as a raw report (e.g., set report =
result.text, insights = [] or extract a best-effort insights string), still log
a parsing warning via logError/logStepEnd, emit the writer?.custom completion
event with a message indicating fallback parsing was used, and return the
constructed object; modify the code around reportAgent.generate,
JSON.parse(result.text), and the returned object to implement this resilient
parsing behavior.
- Around line 130-146: The code creates a sandbox via createSandbox.execute
(assigned to variable sandbox) but never closes it; add a finally block after
the try that ensures the sandbox is cleaned up: if sandbox exists call
sandbox.disconnect() inside its own try/catch and on error call
logError('sandbox-cleanup', error). Alternatively, replace direct disconnect
with a shared utility (e.g., a new closeSandbox tool in src/mastra/tools/e2b.ts)
and call that in the finally to centralize cleanup and error handling.
In @src/mastra/workflows/safe-refactoring-workflow.ts:
- Around line 167-169: The code incorrectly treats the return of
runCommand.execute as possibly being a z.ZodError (the check "execution
instanceof z.ZodError"); tool executions throw errors rather than returning
ZodError instances. Replace that pattern around runCommand.execute: remove the
instanceof check and instead wrap the call in a try/catch, catch errors thrown
by runCommand.execute and if the caught error is a z.ZodError handle it (e.g.,
throw a new Error with the validation message) otherwise rethrow or convert to a
descriptive Error; reference the runCommand.execute invocation and the
z.ZodError type to locate and update the logic.
- Around line 129-133: The code wrongly checks `sandbox instanceof z.ZodError`
after calling `createSandbox.execute`; `createSandbox.execute` either returns `{
sandboxId: string }` or throws an Error, so remove the `instanceof z.ZodError`
branch and do one of two fixes: either let errors thrown by
`createSandbox.execute` propagate (remove the check and directly destructure
`const { sandboxId } = sandbox as { sandboxId: string };`), or replace the check
with a simple runtime type guard (e.g., verify `sandbox && typeof (sandbox as
any).sandboxId === "string"` and throw a clear Error if not). Ensure references
to `sandbox`, `createSandbox.execute`, and `sandboxId` are used to locate and
update the code.
- Around line 65-71: The code incorrectly reads result.object from
refactoringAgent.generate(); refactoringAgent.generate() returns { text: string
} so replace the result.object access with parsing result.text as JSON (e.g.,
JSON.parse(result.text)) and handle JSON parse errors: attempt to parse
result.text into the expected { refactoredCode, explanation } shape, fall back
to { refactoredCode: inputData.sourceCode, explanation: 'Failed to generate
refactor' } if parsing fails or required fields are missing, and update the
assignment currently creating output so it uses the parsed JSON instead of
result.object; focus changes around refactoringAgent.generate, the result
variable, and the output assignment.
In @src/mastra/workflows/test-generation-workflow.ts:
- Around line 150-157: The current test command construction (variable
testCommand in test-generation-workflow.ts using inputData.language and
inputData.testFilePath) assumes npx/pip and network installs will succeed;
instead, either use a pre-baked sandbox image with vitest/pytest installed or
perform the install once during sandbox setup (not inline in testCommand), add
early validation of inputData.language and inputData.testFilePath, and add
runtime checks before executing the command to detect if npx/pip or the test
runner is available and fail fast with a clear error; also document the
environment/network assumption if you must keep inline installs.
- Around line 58-60: The prompt template in test-generation-workflow.ts builds a
markdown code fence using a malformed opening fence string
("``${inputData.language}") which is missing one backtick and will break the
generated prompt; update the template that composes the snippet (where
inputData.language and inputData.code are interpolated) to use a proper triple
backtick opening fence ("```${inputData.language}") so the fenced code block is
valid and closed by the existing closing fence.
- Around line 67-96: The JSON.parse(result.text) call inside the generate-tests
block can throw and bypass your fallback; wrap parsing in its own try/catch so
malformed JSON doesn’t crash the flow: attempt to parse result.text (from
testEngineerAgent.generate) and on a SyntaxError catch it, call
logError('generate-tests', error) (or similar) and set parsed/output to the
existing fallback { testCode: '', testFilePath } so the writer/progress and
return path still run; ensure you reference result.text, parsed, output and
testFilePath when implementing the safe-parse and keep the surrounding
writer?.custom and final return intact.
- Line 86: The call to logStepEnd('generate-tests', {}, Date.now() - startTime)
logs an empty object; replace the empty object with meaningful output (e.g., {
success: true, testFilePath } or { success: true, generatedTestFilePath }) so
the step records whether generation succeeded and the resulting file path;
locate the logStepEnd invocation in the generate-tests step and pass the
appropriate variable(s) that hold the generated test file path (or a success
flag) ensuring those variables are in scope before the call.
- Around line 125-148: The inline checks for an "error" property on E2B tool
results are incorrect because these tools throw on failure; remove the
conditional checks like "if ('error' in sandbox) { throw sandbox.error; }" after
calls to createSandbox.execute and any similar checks after writeFile.execute
(and the other tool call around line ~166) so the outer try/catch handles
exceptions; leave the await calls (createSandbox.execute, writeFile.execute)
intact and rely on thrown exceptions for error flow.
📜 Review details
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Review profile: ASSERTIVE
Plan: Pro
⛔ Files ignored due to path filters (1)
package-lock.jsonis excluded by!**/package-lock.json
📒 Files selected for processing (10)
AGENTS.mdpackage.jsonsrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/safe-refactoring-workflow.tssrc/mastra/workflows/test-generation-workflow.ts
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**/*.{js,jsx,ts,tsx}
📄 CodeRabbit inference engine (.github/instructions/next-js.instructions.md)
**/*.{js,jsx,ts,tsx}: Usenext/dynamicfor dynamic imports to load components only when needed, improving initial load time.
Usenext/imagecomponent for automatic image optimization, including lazy loading and responsive images.
Use React.memo to prevent unnecessary re-renders of components.
Use the<Link prefetch>tag to prefetch pages that are likely to be visited.
Use getServerSideProps, getStaticProps, or server components for fetching data on the server-side.
Use SWR or React Query for client-side data fetching and caching.
Use CSS Modules, Styled Components, or Tailwind CSS for component-level styling. Prefer Tailwind CSS for rapid development.
Use React Context, Zustand, Jotai, or Recoil for managing global state. Avoid Redux unless necessary.
Usereact-hook-formfor managing forms and validation.
Only fetch the data that is needed by the component to avoid over-fetching.
Avoid long-running synchronous operations in the main thread to prevent blocking.
Always usesetStateor hooks to update state instead of mutating state directly.
Include a complete dependency array inuseEffecthooks to prevent unexpected behavior.
Avoid writing server-side code in client components to prevent exposing secrets or causing unexpected behavior.
Usetry...catchblocks for handling errors in asynchronous operations.
Implement error boundary components usinggetDerivedStateFromErrororcomponentDidCatchlifecycle methods.
Sanitize user input to prevent Cross-Site Scripting (XSS) attacks. Be especially careful when rendering HTML directly from user input.
Store authentication tokens in HTTP-only cookies or local storage securely.
Implement role-based access control to restrict access to sensitive resources.
Clean up event listeners and timers inuseEffecthooks to avoid memory leaks.
Only update state when necessary to reduce the number of re-renders and improve performance.
Use immutable data structures and avoid mutating data directly to prevent unexpected...
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tssrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/workflows/safe-refactoring-workflow.ts
**/*.{js,ts}
📄 CodeRabbit inference engine (.github/instructions/next-js.instructions.md)
Use parameterized queries or an ORM to prevent SQL injection attacks.
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tssrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/workflows/safe-refactoring-workflow.ts
**/*.{ts,tsx,js,jsx,py,java,cs,rb,go,rs,cpp,c,h,hpp,swift,kotlin,php,scala,clj,groovy,lua,sh,bash}
📄 CodeRabbit inference engine (.github/instructions/self-explanatory-code-commenting.instructions.md)
**/*.{ts,tsx,js,jsx,py,java,cs,rb,go,rs,cpp,c,h,hpp,swift,kotlin,php,scala,clj,groovy,lua,sh,bash}: Write code that speaks for itself. Comment only when necessary to explain WHY, not WHAT. Avoid obvious comments that state what the code literally does.
Avoid redundant comments that simply repeat what the code is doing
Keep comments accurate and up-to-date with code changes. Remove or update outdated comments that no longer match the implementation.
Write comments for complex business logic that explain the WHY behind specific calculations or business rules
Document non-obvious algorithms with comments explaining the algorithm choice and its reasoning
Add comments explaining what regex patterns match, especially for complex patterns
Document API constraints, rate limits, gotchas, and external dependencies with explanatory comments
Avoid commenting out dead code. Use version control instead of maintaining commented code blocks.
Do not maintain code change history or modification logs as comments. Rely on git history and commit messages instead.
Avoid decorative divider comments (e.g., lines of equals signs or asterisks) for section separation
Ensure comments are placed appropriately above or adjacent to the code they describe
Write comments using proper grammar, spelling, and professional language
Prefer self-documenting code with clear variable/function names over adding comments to explain unclear code
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tssrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/workflows/safe-refactoring-workflow.ts
**/*.{ts,tsx,js,jsx}
📄 CodeRabbit inference engine (.github/instructions/self-explanatory-code-commenting.instructions.md)
**/*.{ts,tsx,js,jsx}: Document public APIs with TSDoc/JSDoc comments including parameter descriptions, return types, examples, and thrown exceptions
Add TSDoc comments to configuration constants and environment variables explaining their source, reasoning, or constraints
Use TSDoc annotation tags (TODO, FIXME, HACK, NOTE, WARNING, PERF, SECURITY, BUG, REFACTOR, DEPRECATED) to mark special comments
Include file headers with @fileoverview, @author, @copyright, and @license tags to document file purpose and ownership
Document function parameters with @param tags, return values with @returns tags, and exceptions with @throws tags in TSDoc comments
Use @see tags in TSDoc comments to reference related functions, methods, or documentation
Include @example tags in public API documentation with code examples showing typical usage
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tssrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/workflows/safe-refactoring-workflow.ts
**/*.{ts,tsx}
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**/*.{ts,tsx}: Document interface and type definitions with TSDoc comments explaining their purpose and usage context
Document interface properties with /** */ comments explaining each field's purpose and constraints
Document generic type parameters with @template tags explaining what each type parameter represents
Use type guards with comments explaining the runtime validation logic being performed
Document advanced/complex TypeScript types with explanatory comments about their purpose and use cases
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tssrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/workflows/safe-refactoring-workflow.ts
src/mastra/**/*
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mastramodules can import fromutils, but must not import fromapporcli(excepttypes)
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tssrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/workflows/safe-refactoring-workflow.ts
src/mastra/workflows/**/*.ts
📄 CodeRabbit inference engine (src/mastra/AGENTS.md)
Add workflows under
src/mastra/workflowsto orchestrate multi-step flows
src/mastra/workflows/**/*.ts: Define workflows using Mastra DSL patterns (e.g.,.then(),.branch(),.parallel(),.foreach(),.dowhile()) and demonstrate the appropriate pattern for your use case
Use tools and agents as building blocks in workflows; prefer composition over duplication
Use sequential pattern (.then()) for workflows with dependent steps executed in order (e.g., weatherWorkflow, stockAnalysisWorkflow, changelogWorkflow)
Use parallel pattern (.parallel()) for workflows that fetch or process multiple independent data sources concurrently (e.g., financialReportWorkflow)
Use conditional branch pattern (.branch()) for workflows that need to route to different processing paths based on input conditions (e.g., documentProcessingWorkflow for PDF handling)
Use loop pattern (.dowhile()) for workflows that need iterative refinement until a condition is met (e.g., contentReviewWorkflow)
Use iteration pattern (.foreach()) for workflows that process multiple items concurrently (e.g., researchSynthesisWorkflow for topic research)
Use human-in-the-loop pattern withsuspend()andresume()for workflows requiring human approval or input (e.g., learningExtractionWorkflow)
Pipe agent response streams to the step writer usingresponse.fullStream.pipeTo(writer)to enable text chunk streaming in workflow steps
UseinputSchemaandoutputSchemawith Zod for type-safe step definitions in workflows
Call.commit()on workflow definitions after constructing them to finalize and register the workflow
Add tests and e2e test harnesses to validate workflow integrationsUse Mastra DSL for defining workflows with multi-step orchestration
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tssrc/mastra/workflows/safe-refactoring-workflow.ts
src/mastra/{tools,workflows}/**/*.ts
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Use
RequestContext(per-request) or agent-specific runtime context types (e.g.EditorRuntimeContext) to enforce access control in tools and workflows
Files:
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Apply Single Responsibility Principle: each function/class does one thing well
Follow DRY (Don't Repeat Yourself): eliminate code duplication
Keep functions small and focused (ideally < 20-30 lines)
Avoid deeply nested code (max 3-4 levels)
Avoid magic numbers and strings; use named constants instead
Code should be self-documenting; use comments only when necessary
Implement proper error handling at appropriate levels with meaningful error messages
Avoid silent failures or ignored exceptions; fail fast and validate inputs early
Use appropriate error types/exceptions with meaningful context
Validate and sanitize all user inputs
Use parameterized queries for database access; never use string concatenation for SQL queries
Implement proper authentication checks before accessing resources
Verify user has permission to perform actions; implement proper authorization
Use established cryptographic libraries; never roll your own crypto implementation
Avoid N+1 query problems; use proper indexing and eager loading for database queries
Use appropriate algorithms with suitable time/space complexity for the use case
Utilize caching for expensive or repeated operations
Ensure proper cleanup of connections, files, and streams to prevent resource leaks
Implement pagination for large result sets
Load data only when needed (lazy loading pattern)
Document all public APIs with purpose, parameters, and return values
Add explanatory comments for non-obvious logic
No commented-out code or unresolved TODO comments without associated tickets should remain in commits
Ensure code follows consistent style and conventions with the rest of the codebase
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tssrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/workflows/safe-refactoring-workflow.ts
**/*.{js,ts,jsx,tsx,java,py,cs,go,rb,php,swift,kt,scala,rs,cpp,c,h,json,yaml,yml,env,config}
📄 CodeRabbit inference engine (.github/instructions/code-review-generic.instructions.md)
Never include passwords, API keys, tokens, or PII in code or logs
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tspackage.jsonsrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/workflows/safe-refactoring-workflow.ts
**/*.{ts,tsx,java,cs,go,php,swift,kt,scala}
📄 CodeRabbit inference engine (.github/instructions/code-review-generic.instructions.md)
Prefer small, focused interfaces (Interface Segregation Principle)
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tssrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/workflows/safe-refactoring-workflow.ts
**/*.{js,mjs,cjs,ts,tsx,jsx,py,java,cs,go,rb,php,rs,cpp,c,h,hpp}
📄 CodeRabbit inference engine (.github/instructions/update-docs-on-code-change.instructions.md)
Use automated documentation generators for code documentation - JSDoc/TSDoc for JavaScript/TypeScript, Sphinx/pdoc for Python, Javadoc for Java, xmldoc for C#, godoc for Go, rustdoc for Rust
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tssrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/workflows/safe-refactoring-workflow.ts
**/*.{css,tsx,ts}
📄 CodeRabbit inference engine (AGENTS.md)
Use Tailwind CSS 4 with oklch color variables for styling
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tssrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/workflows/safe-refactoring-workflow.ts
src/**/*.{ts,tsx}
📄 CodeRabbit inference engine (AGENTS.md)
Run ESLint with npx eslint 'src/**/*.{ts,tsx}' --max-warnings=0 to enforce linting rules
Files:
src/mastra/workflows/data-analysis-workflow.tssrc/mastra/workflows/automated-reporting-workflow.tssrc/mastra/workflows/index.tssrc/mastra/workflows/test-generation-workflow.tssrc/mastra/index.tssrc/mastra/networks/codingTeamNetwork.tssrc/mastra/a2a/codingA2ACoordinator.tssrc/mastra/workflows/safe-refactoring-workflow.ts
**/{package.json,package-lock.json,yarn.lock,pom.xml,build.gradle,Pipfile,Pipfile.lock,requirements.txt,composer.json,composer.lock,pubspec.yaml,Gemfile,Gemfile.lock,go.mod,go.sum,Cargo.toml,Cargo.lock}
📄 CodeRabbit inference engine (.github/instructions/code-review-generic.instructions.md)
Check dependencies for known vulnerabilities and keep them up-to-date
Files:
package.json
src/mastra/index.ts
📄 CodeRabbit inference engine (src/AGENTS.md)
Enforce registration pattern in
mastra/index.tsfor AI orchestration modules composition
Files:
src/mastra/index.ts
src/mastra/networks/**/*.ts
📄 CodeRabbit inference engine (src/mastra/AGENTS.md)
Add networks under
src/mastra/networksto coordinate multiple agents
Files:
src/mastra/networks/codingTeamNetwork.ts
**/*.md
📄 CodeRabbit inference engine (.github/instructions/markdown.instructions.md)
**/*.md: Use appropriate heading levels (H2, H3, etc.) to structure markdown content. Do not use H1 headings, as these will be generated from the title. Use##for H2 and###for H3 in a hierarchical manner. Recommend restructuring if content includes H4 or higher levels.
Use bullet points (with-) or numbered lists (with1.) for lists in markdown. Indent nested lists with two spaces and ensure proper indentation and spacing.
Use fenced code blocks (triple backticks) for code snippets in markdown. Specify the language after the opening backticks for syntax highlighting (e.g.,csharp).
Use proper markdown syntax for links:[link text](URL). Ensure that link text is descriptive and URLs are valid and accessible.
Use proper markdown syntax for images:. Include a brief description of the image in the alt text for accessibility.
Use markdown tables (with|delimiters) for tabular data. Ensure proper formatting, alignment, and inclusion of headers.
Limit line length to 80 characters in markdown for readability. Use soft line breaks for long paragraphs.
Use appropriate whitespace in markdown to separate sections and improve readability. Use blank lines between sections and avoid excessive whitespace.
Include YAML front matter at the beginning of markdown files with required metadata fields:post_title,author1,post_slug,microsoft_alias,featured_image,categories(from /categories.txt),tags,ai_note,summary, andpost_date.
Files:
AGENTS.md
src/mastra/a2a/**/*.ts
📄 CodeRabbit inference engine (AGENTS.md)
Implement Agent-to-Agent (A2A) coordination in src/mastra/a2a for multi-agent orchestration
Files:
src/mastra/a2a/codingA2ACoordinator.ts
🧬 Code graph analysis (3)
src/mastra/workflows/data-analysis-workflow.ts (3)
src/mastra/config/logger.ts (2)
logStepStart(72-88)logStepEnd(90-109)src/mastra/tools/e2b.ts (3)
createSandbox(5-36)writeFile(109-135)runCode(38-80)src/mastra/workflows/index.ts (1)
dataAnalysisWorkflow(16-16)
src/mastra/workflows/automated-reporting-workflow.ts (2)
src/mastra/config/agent-schemas.ts (1)
reportOutputSchema(136-138)src/mastra/config/logger.ts (3)
logStepStart(72-88)logStepEnd(90-109)logError(153-174)
src/mastra/workflows/test-generation-workflow.ts (3)
src/mastra/config/logger.ts (2)
logStepStart(72-88)logStepEnd(90-109)src/mastra/tools/e2b.ts (3)
createSandbox(5-36)writeFile(109-135)runCommand(476-519)src/mastra/workflows/index.ts (1)
testGenerationWorkflow(15-15)
🪛 LanguageTool
AGENTS.md
[uncategorized] ~326-~326: The official name of this software platform is spelled with a capital “H”.
Context: ...d. ## Cursor/Copilot Rules Located in .github/copilot-instructions.md: - 🧠 Read `/...
(GITHUB)
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (5)
- GitHub Check: Agent
- GitHub Check: CodeQL analysis (javascript-typescript)
- GitHub Check: Sourcery review
- GitHub Check: Codacy Security Scan
- GitHub Check: Analyze (javascript-typescript)
🔇 Additional comments (15)
AGENTS.md (2)
1-1: LGTM: Version metadata updated appropriately.The version bump from 2.3.0 to 2.4.0 aligns with the significant documentation enhancements introduced in this PR.
92-466: Excellent documentation enhancement with comprehensive guidelines.The new code style guidelines, testing standards, and implementation patterns provide valuable reference material for contributors. The examples are well-structured with proper markdown formatting and language-specific code blocks.
src/mastra/workflows/test-generation-workflow.ts (1)
205-214: LGTM: Workflow composition follows Mastra DSL patterns correctly.The workflow uses the sequential
.then()pattern appropriately for dependent steps and properly calls.commit()to finalize the workflow definition.As per coding guidelines, this follows the recommended pattern for workflows with dependent steps executed in order.
src/mastra/index.ts (1)
117-118: LGTM: New workflows registered correctly.The
dataAnalysisWorkflowandautomatedReportingWorkflowimports and registrations follow the established pattern used by other workflows in the Mastra instance.Also applies to: 136-137
src/mastra/workflows/index.ts (1)
14-17: LGTM: New workflow exports added correctly.The four new workflow exports follow the established pattern and align with the new workflow modules introduced in this PR.
package.json (1)
46-171: All dependency versions verified and secure.The updated package versions (@ai-sdk/google-vertex@4.0.7, @ai-sdk/openai@3.0.7, @ai-sdk/openai-compatible@2.0.4, @ai-sdk/react@3.0.13, framer-motion@12.24.7, motion@12.24.7, react-resizable-panels@4.2.2, and streamdown@1.6.11) all exist on the npm registry and the project has no known security vulnerabilities (npm audit: 0 vulnerabilities).
src/mastra/workflows/automated-reporting-workflow.ts (2)
144-153: Good fallback handling for JSON parsing failures.The nested try-catch with a sensible fallback ensures the workflow can continue even if the agent returns malformed JSON. This is a robust pattern for handling LLM outputs.
185-194: Workflow composition follows Mastra DSL patterns correctly.The sequential
.then()pattern is appropriate here sincesynthesizeReportStepdepends on the output ofresearchTopicStep. The workflow is properly committed.src/mastra/a2a/codingA2ACoordinator.ts (2)
18-21: New workflow imports are correctly added.The imports for the four new workflows are properly structured and follow the existing import patterns in the file.
199-202: Workflows are correctly registered in the coordinator.All four new workflows are properly added to the
workflowsconfiguration object, making them available for orchestration.src/mastra/workflows/data-analysis-workflow.ts (2)
186-192: Good OpenTelemetry span management in error path.The span properly records exceptions, sets error status, and ends the span before rethrowing. This ensures traces are complete even on failure.
271-281: Workflow composition correctly follows sequential pattern.The three-step pipeline appropriately uses
.then()chaining since each step depends on the previous step's output. The workflow is properly committed.src/mastra/networks/codingTeamNetwork.ts (1)
29-86: Well-structured instructions with clear agent registry and operational logic.The rewritten instructions provide a formal, comprehensive guide for the network coordinator with:
- Clear role definition and capabilities
- Detailed agent registry with triggers and use cases
- Standard chains for common tasks (Feature Build, Security Fix, Optimization)
- Explicit constraints and success criteria
This is a significant improvement over ad-hoc routing guidance.
src/mastra/workflows/safe-refactoring-workflow.ts (2)
203-215: Good graceful degradation on verification failure.The catch block returns unverified code with error details instead of failing the entire workflow. This ensures users still get refactored code even if sandbox verification fails, which is a pragmatic approach.
219-228: Workflow composition follows correct pattern.The two-step sequential workflow using
.then()is appropriate since verification depends on the generated refactored code. The workflow is properly committed.
| This coordinator also exposes higher-level workflows: | ||
| - **researchSynthesisWorkflow**: Multi-topic research synthesis | ||
| - **specGenerationWorkflow**: SPARC-based spec generation | ||
| - **repoIngestionWorkflow**: Ingest repositories for RAG | ||
| - **learningExtractionWorkflow**: Extract learnings from documents | ||
| - **financialReportWorkflow**: Financial analysis reports | ||
| - **safeRefactoringWorkflow**: Refactor code with E2B sandbox verification | ||
| - **testGenerationWorkflow**: Generate and verify tests in E2B sandbox | ||
|
|
||
| When a user's request requires prolonged, structured work across multiple subtasks, prefer invoking these workflows and orchestrating agents around them.`, |
There was a problem hiding this comment.
Workflow documentation is incomplete - missing two workflows.
The instructions list safeRefactoringWorkflow and testGenerationWorkflow but omit dataAnalysisWorkflow and automatedReportingWorkflow, even though all four are registered in the workflows object (lines 199-202). This inconsistency could confuse users about available capabilities.
🔎 Proposed fix to add missing workflow descriptions
This coordinator also exposes higher-level workflows:
- **researchSynthesisWorkflow**: Multi-topic research synthesis
- **specGenerationWorkflow**: SPARC-based spec generation
- **repoIngestionWorkflow**: Ingest repositories for RAG
- **learningExtractionWorkflow**: Extract learnings from documents
- **financialReportWorkflow**: Financial analysis reports
- **safeRefactoringWorkflow**: Refactor code with E2B sandbox verification
- **testGenerationWorkflow**: Generate and verify tests in E2B sandbox
+- **dataAnalysisWorkflow**: Production-grade data analysis using E2B sandboxes
+- **automatedReportingWorkflow**: Multi-section research synthesis into professional reports📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| This coordinator also exposes higher-level workflows: | |
| - **researchSynthesisWorkflow**: Multi-topic research synthesis | |
| - **specGenerationWorkflow**: SPARC-based spec generation | |
| - **repoIngestionWorkflow**: Ingest repositories for RAG | |
| - **learningExtractionWorkflow**: Extract learnings from documents | |
| - **financialReportWorkflow**: Financial analysis reports | |
| - **safeRefactoringWorkflow**: Refactor code with E2B sandbox verification | |
| - **testGenerationWorkflow**: Generate and verify tests in E2B sandbox | |
| When a user's request requires prolonged, structured work across multiple subtasks, prefer invoking these workflows and orchestrating agents around them.`, | |
| This coordinator also exposes higher-level workflows: | |
| - **researchSynthesisWorkflow**: Multi-topic research synthesis | |
| - **specGenerationWorkflow**: SPARC-based spec generation | |
| - **repoIngestionWorkflow**: Ingest repositories for RAG | |
| - **learningExtractionWorkflow**: Extract learnings from documents | |
| - **financialReportWorkflow**: Financial analysis reports | |
| - **safeRefactoringWorkflow**: Refactor code with E2B sandbox verification | |
| - **testGenerationWorkflow**: Generate and verify tests in E2B sandbox | |
| - **dataAnalysisWorkflow**: Production-grade data analysis using E2B sandboxes | |
| - **automatedReportingWorkflow**: Multi-section research synthesis into professional reports |
🤖 Prompt for AI Agents
In @src/mastra/a2a/codingA2ACoordinator.ts around lines 162 - 171, The
documentation block listing high-level workflows is missing descriptions for
dataAnalysisWorkflow and automatedReportingWorkflow; update the comment where
the workflows are described (the block that currently lists
researchSynthesisWorkflow, specGenerationWorkflow, repoIngestionWorkflow,
learningExtractionWorkflow, financialReportWorkflow, safeRefactoringWorkflow,
testGenerationWorkflow) to include concise descriptions for dataAnalysisWorkflow
and automatedReportingWorkflow so the comment matches the actual registered
workflows in the workflows object and eliminates the inconsistency.
| ## HIGH-LEVEL WORKFLOW REGISTRY | ||
| Invoke these for structured, multi-phase processes: | ||
| - **researchSynthesisWorkflow:** For multi-topic research and data synthesis. | ||
| - **specGenerationWorkflow:** For creating comprehensive technical specifications. | ||
| - **repoIngestionWorkflow:** For ingesting repository content into RAG pipelines. | ||
| - **learningExtractionWorkflow:** For human-in-the-loop knowledge extraction. | ||
| - **financialReportWorkflow:** For generating structured financial analysis. |
There was a problem hiding this comment.
🧩 Analysis chain
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rg -n "safeRefactoringWorkflow|testGenerationWorkflow|dataAnalysisWorkflow|automatedReportingWorkflow" src/mastra/networks/codingTeamNetwork.ts
# Also check what's in the file around lines 60-66 and the workflows object
echo -e "\n=== Reading codingTeamNetwork.ts to see workflows object ==="
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Add missing workflows to codingTeamNetwork or document architectural rationale.
The 4 new workflows (safeRefactoringWorkflow, testGenerationWorkflow, dataAnalysisWorkflow, automatedReportingWorkflow) are imported and available in codingA2ACoordinator but missing from codingTeamNetwork. Lines 60-66 document only the original 5 workflows, and the workflows object (lines 99-105) doesn't include the new ones.
If codingTeamNetwork should also support these workflows, add the imports (lines 1-11) and include them in both the instructions registry and the workflows object. If the different workflow sets are intentional due to different architectural roles (routing vs. parallel orchestration), this should be documented in a comment or design document explaining the separation.
🤖 Prompt for AI Agents
In @src/mastra/networks/codingTeamNetwork.ts around lines 60 - 66, The
HIGH-LEVEL WORKFLOW REGISTRY in codingTeamNetwork is missing the four workflows
(safeRefactoringWorkflow, testGenerationWorkflow, dataAnalysisWorkflow,
automatedReportingWorkflow) that are imported and used in codingA2ACoordinator;
update codingTeamNetwork to either (A) import those four symbols and add them to
the registry text block and to the exported workflows object (the "workflows"
variable) so routing supports them, or (B) if omission is intentional, add a
concise comment above the registry explaining the architectural separation
between codingTeamNetwork (routing) and codingA2ACoordinator (parallel
orchestration) and why these workflows are only registered there. Ensure
references to the symbols safeRefactoringWorkflow, testGenerationWorkflow,
dataAnalysisWorkflow, automatedReportingWorkflow, codingA2ACoordinator, and the
workflows object are consistent.
| const reportInputSchema = z.object({ | ||
| topic: z.string().describe('The main topic of the report'), | ||
| sections: z.array(z.string()).describe('List of sections to include in the report'), | ||
| depth: z.enum(['brief', 'detailed', 'comprehensive']).default('detailed'), | ||
| }); | ||
|
|
||
| const reportOutputSchema = z.object({ | ||
| reportId: z.string(), | ||
| title: z.string(), | ||
| executiveSummary: z.string(), | ||
| fullReport: z.string(), | ||
| metadata: z.object({ | ||
| topic: z.string(), | ||
| generatedAt: z.string(), | ||
| sectionsCount: z.number(), | ||
| }), | ||
| }); |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Consider reusing existing reportOutputSchema from agent-schemas.ts.
There's already a reportOutputSchema defined in src/mastra/config/agent-schemas.ts (lines 135-137). While that schema is simpler, having two schemas with the same name in the codebase can cause confusion. Consider either:
- Renaming this local schema to something more specific (e.g.,
automatedReportOutputSchema) - Extending the existing schema if appropriate
🤖 Prompt for AI Agents
In @src/mastra/workflows/automated-reporting-workflow.ts around lines 7 - 23,
The local reportOutputSchema in automated-reporting-workflow.ts duplicates the
name of an existing reportOutputSchema in src/mastra/config/agent-schemas.ts;
rename or reuse it to avoid confusion. Either rename the local symbol (e.g.,
automatedReportOutputSchema) and update any references in this file
(reportOutputSchema -> automatedReportOutputSchema), or import and extend the
shared reportOutputSchema from agent-schemas.ts (use extension/merge logic and
update references) so there aren’t two different exports with the same name.
| outputSchema: z.object({ | ||
| topic: z.string(), | ||
| sections: z.array(z.object({ | ||
| name: z.string(), | ||
| data: z.string(), | ||
| })), | ||
| depth: z.string(), | ||
| }), |
There was a problem hiding this comment.
Output schema depth type mismatch with input schema.
The inputSchema defines depth as z.enum(['brief', 'detailed', 'comprehensive']), but the outputSchema declares it as z.string(). This loses type information and could lead to unexpected values downstream.
🔎 Proposed fix
outputSchema: z.object({
topic: z.string(),
sections: z.array(z.object({
name: z.string(),
data: z.string(),
})),
- depth: z.string(),
+ depth: z.enum(['brief', 'detailed', 'comprehensive']),
}),📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| outputSchema: z.object({ | |
| topic: z.string(), | |
| sections: z.array(z.object({ | |
| name: z.string(), | |
| data: z.string(), | |
| })), | |
| depth: z.string(), | |
| }), | |
| outputSchema: z.object({ | |
| topic: z.string(), | |
| sections: z.array(z.object({ | |
| name: z.string(), | |
| data: z.string(), | |
| })), | |
| depth: z.enum(['brief', 'detailed', 'comprehensive']), | |
| }), |
🤖 Prompt for AI Agents
In @src/mastra/workflows/automated-reporting-workflow.ts around lines 29 - 36,
The outputSchema currently types depth as z.string() which mismatches the
inputSchema's depth defined as z.enum(['brief','detailed','comprehensive']);
update outputSchema to use the same enum (e.g., replace depth: z.string() with
depth: z.enum(['brief','detailed','comprehensive']) or reuse a shared
constant/variable for the enum) so both inputSchema and outputSchema enforce
identical allowed depth values; ensure you reference the same symbol (the enum
or sharedDepth constant) to avoid duplication.
| for (const section of inputData.sections) { | ||
| await writer?.custom({ | ||
| type: 'data-tool-progress', | ||
| data: { | ||
| status: 'in-progress', | ||
| message: `Researching section: ${section}...`, | ||
| stage: 'research-topic', | ||
| }, | ||
| id: 'research-topic', | ||
| }); | ||
|
|
||
| const prompt = `Research the following aspect of "${inputData.topic}": ${section}. | ||
| Provide a ${inputData.depth} summary of key facts, trends, and data points.`; | ||
|
|
||
| const result = await researchAgent.generate(prompt); | ||
| researchedSections.push({ | ||
| name: section, | ||
| data: result.text, | ||
| }); | ||
| } |
There was a problem hiding this comment.
🧹 Nitpick | 🔵 Trivial
Sequential section research lacks error handling for partial failures.
If researchAgent.generate() fails for one section, the entire step fails with no partial results preserved. For a multi-section research task, consider wrapping each iteration in try-catch to collect partial results or use Promise.allSettled for parallel execution with graceful degradation.
🔎 Proposed improvement for resilience
for (const section of inputData.sections) {
await writer?.custom({
type: 'data-tool-progress',
data: {
status: 'in-progress',
message: `Researching section: ${section}...`,
stage: 'research-topic',
},
id: 'research-topic',
});
const prompt = `Research the following aspect of "${inputData.topic}": ${section}.
Provide a ${inputData.depth} summary of key facts, trends, and data points.`;
- const result = await researchAgent.generate(prompt);
- researchedSections.push({
- name: section,
- data: result.text,
- });
+ try {
+ const result = await researchAgent.generate(prompt);
+ researchedSections.push({
+ name: section,
+ data: result.text,
+ });
+ } catch (error) {
+ logError('research-topic', error, { section });
+ researchedSections.push({
+ name: section,
+ data: `[Research failed for this section: ${error instanceof Error ? error.message : 'Unknown error'}]`,
+ });
+ }
}| \`\`${inputData.language} | ||
| ${inputData.code} | ||
| \`\`\` |
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Fix malformed code fence in prompt.
The opening code fence on line 58 is missing the third backtick, which will likely confuse the AI agent and result in malformed test generation.
🔎 Proposed fix
Code:
- \`\`${inputData.language}
+ \`\`\`${inputData.language}
${inputData.code}
\`\`\`📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| \`\`${inputData.language} | |
| ${inputData.code} | |
| \`\`\` | |
| \`\`\`${inputData.language} | |
| ${inputData.code} | |
| \`\`\` |
🤖 Prompt for AI Agents
In @src/mastra/workflows/test-generation-workflow.ts around lines 58 - 60, The
prompt template in test-generation-workflow.ts builds a markdown code fence
using a malformed opening fence string ("``${inputData.language}") which is
missing one backtick and will break the generated prompt; update the template
that composes the snippet (where inputData.language and inputData.code are
interpolated) to use a proper triple backtick opening fence
("```${inputData.language}") so the fenced code block is valid and closed by the
existing closing fence.
| try { | ||
| const result = await testEngineerAgent.generate(prompt); | ||
|
|
||
| const parsed = JSON.parse(result.text); | ||
| const output = parsed ?? { | ||
| testCode: '', | ||
| testFilePath | ||
| }; | ||
|
|
||
| await writer?.custom({ | ||
| type: 'data-tool-progress', | ||
| data: { | ||
| status: 'done', | ||
| message: `Tests generated.`, | ||
| stage: 'generate-tests', | ||
| }, | ||
| id: 'generate-tests', | ||
| }); | ||
|
|
||
| logStepEnd('generate-tests', {}, Date.now() - startTime); | ||
|
|
||
| return { | ||
| ...inputData, | ||
| testCode: output.testCode, | ||
| testFilePath: output.testFilePath ?? testFilePath, | ||
| }; | ||
| } catch (error) { | ||
| logError('generate-tests', error); | ||
| throw error; | ||
| } |
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Improve error handling for JSON parsing.
The JSON.parse call on line 70 can throw a SyntaxError if the agent returns malformed JSON, but it's not wrapped in a try-catch block. The fallback logic on lines 71-74 will never execute because the exception will bypass it.
🔎 Proposed fix
try {
const result = await testEngineerAgent.generate(prompt);
- const parsed = JSON.parse(result.text);
- const output = parsed ?? {
- testCode: '',
- testFilePath
- };
+ let output;
+ try {
+ const parsed = JSON.parse(result.text);
+ output = parsed ?? { testCode: '', testFilePath };
+ } catch (parseError) {
+ logError('generate-tests-parse', parseError);
+ output = { testCode: '', testFilePath };
+ }
await writer?.custom({
type: 'data-tool-progress',📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| try { | |
| const result = await testEngineerAgent.generate(prompt); | |
| const parsed = JSON.parse(result.text); | |
| const output = parsed ?? { | |
| testCode: '', | |
| testFilePath | |
| }; | |
| await writer?.custom({ | |
| type: 'data-tool-progress', | |
| data: { | |
| status: 'done', | |
| message: `Tests generated.`, | |
| stage: 'generate-tests', | |
| }, | |
| id: 'generate-tests', | |
| }); | |
| logStepEnd('generate-tests', {}, Date.now() - startTime); | |
| return { | |
| ...inputData, | |
| testCode: output.testCode, | |
| testFilePath: output.testFilePath ?? testFilePath, | |
| }; | |
| } catch (error) { | |
| logError('generate-tests', error); | |
| throw error; | |
| } | |
| try { | |
| const result = await testEngineerAgent.generate(prompt); | |
| let output; | |
| try { | |
| const parsed = JSON.parse(result.text); | |
| output = parsed ?? { testCode: '', testFilePath }; | |
| } catch (parseError) { | |
| logError('generate-tests-parse', parseError); | |
| output = { testCode: '', testFilePath }; | |
| } | |
| await writer?.custom({ | |
| type: 'data-tool-progress', | |
| data: { | |
| status: 'done', | |
| message: `Tests generated.`, | |
| stage: 'generate-tests', | |
| }, | |
| id: 'generate-tests', | |
| }); | |
| logStepEnd('generate-tests', {}, Date.now() - startTime); | |
| return { | |
| ...inputData, | |
| testCode: output.testCode, | |
| testFilePath: output.testFilePath ?? testFilePath, | |
| }; | |
| } catch (error) { | |
| logError('generate-tests', error); | |
| throw error; | |
| } |
🤖 Prompt for AI Agents
In @src/mastra/workflows/test-generation-workflow.ts around lines 67 - 96, The
JSON.parse(result.text) call inside the generate-tests block can throw and
bypass your fallback; wrap parsing in its own try/catch so malformed JSON
doesn’t crash the flow: attempt to parse result.text (from
testEngineerAgent.generate) and on a SyntaxError catch it, call
logError('generate-tests', error) (or similar) and set parsed/output to the
existing fallback { testCode: '', testFilePath } so the writer/progress and
return path still run; ensure you reference result.text, parsed, output and
testFilePath when implementing the safe-parse and keep the surrounding
writer?.custom and final return intact.
| id: 'generate-tests', | ||
| }); | ||
|
|
||
| logStepEnd('generate-tests', {}, Date.now() - startTime); |
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🧹 Nitpick | 🔵 Trivial
Log meaningful output data instead of empty object.
Line 86 logs an empty object {} for the output parameter of logStepEnd. Consider logging meaningful data such as testFilePath or a success indicator to improve traceability.
🔎 Proposed fix
- logStepEnd('generate-tests', {}, Date.now() - startTime);
+ logStepEnd('generate-tests', { testFilePath: output.testFilePath }, Date.now() - startTime);Committable suggestion skipped: line range outside the PR's diff.
🤖 Prompt for AI Agents
In @src/mastra/workflows/test-generation-workflow.ts at line 86, The call to
logStepEnd('generate-tests', {}, Date.now() - startTime) logs an empty object;
replace the empty object with meaningful output (e.g., { success: true,
testFilePath } or { success: true, generatedTestFilePath }) so the step records
whether generation succeeded and the resulting file path; locate the logStepEnd
invocation in the generate-tests step and pass the appropriate variable(s) that
hold the generated test file path (or a success flag) ensuring those variables
are in scope before the call.
| try { | ||
| // 1. Create Sandbox | ||
| const sandbox = await createSandbox.execute({ | ||
| timeoutMS: 300_000, | ||
| }, { mastra, requestContext }); | ||
|
|
||
| if ('error' in sandbox) { throw sandbox.error; } | ||
|
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| const { sandboxId } = sandbox; | ||
|
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||
| // 2. Write source file | ||
| await writeFile.execute({ | ||
| sandboxId, | ||
| path: inputData.filePath, | ||
| content: inputData.code, | ||
| }, { mastra, requestContext }); | ||
|
|
||
| // 3. Write test file | ||
| await writeFile.execute({ | ||
| sandboxId, | ||
| path: inputData.testFilePath, | ||
| content: inputData.testCode, | ||
| }, { mastra, requestContext }); | ||
|
|
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Remove incorrect error handling pattern for E2B tools.
Lines 131 and 166 check for an error property in the tool execution results, but based on the relevant code snippets from src/mastra/tools/e2b.ts, these tools throw errors rather than returning error objects. The outer try-catch block (lines 125-201) already handles exceptions, so these inline error checks are unnecessary and misleading.
🔎 Proposed fix
// 1. Create Sandbox
const sandbox = await createSandbox.execute({
timeoutMS: 300_000,
}, { mastra, requestContext });
- if ('error' in sandbox) { throw sandbox.error; }
-
const { sandboxId } = sandbox;
// 2. Write source fileApply the same fix around line 166:
const execution = await runCommand.execute({
sandboxId,
command: testCommand,
timeoutMs: 120000,
captureOutput: true,
}, { mastra, requestContext });
- if ('error' in execution) { throw execution.error; }
-
await writer?.custom({🤖 Prompt for AI Agents
In @src/mastra/workflows/test-generation-workflow.ts around lines 125 - 148, The
inline checks for an "error" property on E2B tool results are incorrect because
these tools throw on failure; remove the conditional checks like "if ('error' in
sandbox) { throw sandbox.error; }" after calls to createSandbox.execute and any
similar checks after writeFile.execute (and the other tool call around line
~166) so the outer try/catch handles exceptions; leave the await calls
(createSandbox.execute, writeFile.execute) intact and rely on thrown exceptions
for error flow.
| let testCommand = ''; | ||
| if (inputData.language === 'ts' || inputData.language === 'js') { | ||
| // Install vitest if needed, but for speed we'll assume npx works | ||
| // We might need a package.json or just run npx vitest directly | ||
| testCommand = `npx -y vitest run ${inputData.testFilePath}`; | ||
| } else if (inputData.language === 'python') { | ||
| testCommand = `pip install pytest && pytest ${inputData.testFilePath}`; | ||
| } |
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🧹 Nitpick | 🔵 Trivial
Consider pre-installed test frameworks in sandbox environment.
The test commands on lines 154 and 156 assume that npx and pip are available and that packages can be installed on-demand. This approach may be slow (especially pip install) or fail in restricted network environments.
Consider either:
- Using a pre-configured sandbox image with test frameworks installed
- Installing dependencies once during sandbox setup rather than in the test command
- Documenting the assumption that the E2B sandbox has network access
Additionally, the hard-coded commands don't account for potential failures or alternative test runners. Verify whether the E2B sandbox environment supports these commands reliably.
As per coding guidelines, validate inputs and assumptions early to fail fast.
🤖 Prompt for AI Agents
In @src/mastra/workflows/test-generation-workflow.ts around lines 150 - 157, The
current test command construction (variable testCommand in
test-generation-workflow.ts using inputData.language and inputData.testFilePath)
assumes npx/pip and network installs will succeed; instead, either use a
pre-baked sandbox image with vitest/pytest installed or perform the install once
during sandbox setup (not inline in testCommand), add early validation of
inputData.language and inputData.testFilePath, and add runtime checks before
executing the command to detect if npx/pip or the test runner is available and
fail fast with a clear error; also document the environment/network assumption
if you must keep inline installs.
1 participant
Summary by Sourcery
Add new automated data analysis, safe refactoring, test generation, and reporting workflows to the Mastra coding orchestration system and wire them into the coordinator and workflow index while updating documentation and dependencies.
New Features:
Enhancements:
Build: