🤖 CodeRabbit AI Integration - Comprehensive Code Review Setup#1
🤖 CodeRabbit AI Integration - Comprehensive Code Review Setup#1marcusquinn merged 2 commits intomainfrom
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✅ CODERABBIT CONFIGURATION: - Added comprehensive .coderabbit.yaml configuration - Defined review focus areas for DevOps framework - Configured path-specific review instructions - Enabled security, performance, and best practices analysis ✅ QUALITY METRICS UPDATE: - Updated README with ZERO TECHNICAL DEBT achievement - Documented 100% issue resolution (349 → 0 issues) - Highlighted 100% technical debt elimination (805 → 0 minutes) - Updated CodeRabbit integration status ✅ CODE QUALITY SHOWCASE: - Enhanced setup-wizard-helper.sh documentation - Added comprehensive header with usage instructions - Demonstrated adherence to documentation standards - Showcased systematic code quality improvements 🎯 PURPOSE: Trigger comprehensive CodeRabbit AI review 📊 ACHIEVEMENT: Zero technical debt across 18,000+ lines of code 🚀 INTEGRATION: Multi-platform quality assurance (SonarCloud + CodeFactor + CodeRabbit) 🔍 FOCUS: Security, maintainability, and DevOps best practices analysis
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Caution Review failedThe pull request is closed. Warning
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| Cohort / File(s) | Change Summary |
|---|---|
CodeRabbit configuration .coderabbit.yaml |
New CodeRabbit config defining review rules, path-specific guidance for shell scripts, language settings (ShellCheck-style), enabled review features, exclusion patterns, and workflow preferences (auto-approve disabled, request_changes_workflow enabled). |
CLI integration & hooks .agent/scripts/coderabbit-cli.sh, .agent/scripts/pre-commit-hook.sh, .agent/scripts/quality-check.sh |
Added coderabbit-cli.sh (install/setup/review/analyze/status/help workflows, API key management, colored output). Pre-commit hook optionally runs the CLI review if configured. quality-check.sh gains check_coderabbit_cli() and invokes it from main. |
Documentation & guides AGENTS.md, README.md, setup.sh |
AGENTS.md documents CodeRabbit CLI usage and shell-script best practices. README.md updated: adds CodeRabbit PR Reviews badge, replaces previous metric lines with "ZERO TECHNICAL DEBT ACHIEVED" and "100% Technical Debt Elimination", and marks CodeRabbit as configured. setup.sh Next Steps reordered to include CLI install/setup step. |
Script header docs providers/setup-wizard-helper.sh |
Prepended a comprehensive header comment block (usage, commands, author/version/license). No functional changes. |
Sequence Diagram(s)
sequenceDiagram
participant Dev as Developer / CI
participant Local as coderabbit-cli.sh
participant CR as coderabbit (CLI/API)
rect `#DFF5E1`
Dev->>Local: bash .agent/scripts/coderabbit-cli.sh setup
Local->>CR: install / configure (downloads, saves API key)
CR-->>Local: install & token confirmation
Local-->>Dev: success/info messages
end
rect `#F0F7FF`
Dev->>Local: bash .agent/scripts/coderabbit-cli.sh review
Local->>CR: coderabbit review <target>
CR-->>Local: review results (stdout/json)
Local-->>Dev: prints results / exit code
end
Note over Local,CR: Pre-commit/quality-check call the Local script when present
Estimated code review effort
🎯 3 (Moderate) | ⏱️ ~25 minutes
- Areas to focus:
.agent/scripts/coderabbit-cli.sh— verify secure API key handling, permission bits, error paths, and idempotency of install/setup flows..agent/scripts/pre-commit-hook.shand.agent/scripts/quality-check.sh— confirm non-blocking behavior and correct integration when CLI absent..coderabbit.yaml— validate YAML syntax, path globs, and that exclusion rules don't omit desired files.README.md— ensure metric claims are accurate and intentional.
Possibly related PRs
- 🤖 CodeRabbit AI Integration - Comprehensive Code Review Setup #1 — appears to introduce the same CodeRabbit integration (config, CLI, docs, README metric edits) and is likely the directly related PR.
Poem
🐰 I hopped into scripts at dawn,
Wrote keys and badges on the lawn.
Reviews now hum, the CLI sings,
Zero debt and helpful things.
Hop, review, and carry on! 🥕
Pre-merge checks and finishing touches
❌ Failed checks (1 inconclusive)
| Check name | Status | Explanation | Resolution |
|---|---|---|---|
| Title check | ❓ Inconclusive | The title includes an emoji (🤖) which adds noise, and is overly broad. While it describes the general topic (CodeRabbit integration), it doesn't clearly highlight the primary change or distinguish this PR from other potential integration work. | Remove the emoji and make the title more specific about the key change. For example: 'Add CodeRabbit AI review configuration with shell script analysis' or 'Configure CodeRabbit with comprehensive code review rules.' |
✅ Passed checks (2 passed)
| Check name | Status | Explanation |
|---|---|---|
| Description Check | ✅ Passed | Check skipped - CodeRabbit’s high-level summary is enabled. |
| Docstring Coverage | ✅ Passed | No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check. |
📜 Recent review details
Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (6)
.agent/scripts/coderabbit-cli.sh(1 hunks).agent/scripts/pre-commit-hook.sh(1 hunks).agent/scripts/quality-check.sh(2 hunks)AGENTS.md(1 hunks)README.md(3 hunks)setup.sh(1 hunks)
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Comment @coderabbitai help to get the list of available commands and usage tips.
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Actionable comments posted: 5
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (3)
.coderabbit.yaml(1 hunks)README.md(2 hunks)providers/setup-wizard-helper.sh(1 hunks)
⏰ 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). (1)
- GitHub Check: Codacy Static Code Analysis
🔇 Additional comments (2)
providers/setup-wizard-helper.sh (1)
3-18: Clean documentation enhancement. The comprehensive header adds valuable usage guidance without altering functionality. Well-structured comments following shell script conventions.README.md (1)
461-462: Verify metric accuracy before publication. The updated metrics claim complete resolution (349 → 0 issues, 805 → 0 minutes debt), a significant improvement that should be validated against actual analysis tool outputs (SonarCloud, CodeFactor, Codacy) to confirm reproducibility and prevent misleading claims about code quality.
| # CodeRabbit Configuration for AI-Assisted DevOps Framework | ||
| # https://docs.coderabbit.ai/guides/review-instructions | ||
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| # Review Instructions | ||
| reviews: | ||
| # High-level review focus areas | ||
| high_level_summary: true | ||
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| # Specific areas of focus for this DevOps framework | ||
| review_instructions: | | ||
| This is an AI-Assisted DevOps Framework with comprehensive automation tools. | ||
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| Please focus on: | ||
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| **Shell Script Quality:** | ||
| - Proper error handling and return statements | ||
| - Consistent variable naming and local variable usage | ||
| - Security best practices (no hardcoded credentials) | ||
| - Proper quoting and parameter expansion | ||
| - ShellCheck compliance | ||
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| **Architecture & Design:** | ||
| - Modular design and separation of concerns | ||
| - Consistent patterns across provider helpers | ||
| - Clear function responsibilities | ||
| - Proper abstraction levels | ||
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| **Documentation & Maintainability:** | ||
| - Clear function and script documentation | ||
| - Consistent coding style | ||
| - Meaningful variable and function names | ||
| - Proper commenting for complex logic | ||
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| **Security & Best Practices:** | ||
| - No sensitive data in code | ||
| - Proper input validation | ||
| - Safe file operations | ||
| - Secure API interactions | ||
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| **DevOps Automation:** | ||
| - Quality assurance automation | ||
| - CI/CD pipeline effectiveness | ||
| - Multi-platform compatibility | ||
| - Error handling in automation scripts | ||
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| # Auto-approve simple changes | ||
| auto_approve: | ||
| enabled: false # Keep manual review for this critical framework | ||
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| # Request changes for critical issues | ||
| request_changes_workflow: | ||
| enabled: true | ||
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| # Path-specific instructions | ||
| path_instructions: | ||
| - path: "providers/*.sh" | ||
| instructions: | | ||
| Provider helper scripts - focus on: | ||
| - Consistent API patterns | ||
| - Proper error handling | ||
| - Security of credential handling | ||
| - Input validation | ||
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| - path: ".agent/scripts/*.sh" | ||
| instructions: | | ||
| Automation scripts - focus on: | ||
| - Reliability and robustness | ||
| - Clear logging and feedback | ||
| - Proper exit codes | ||
| - Error recovery mechanisms | ||
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| - path: "templates/*.sh" | ||
| instructions: | | ||
| Template scripts - focus on: | ||
| - Security (prompt injection protection) | ||
| - Flexibility and reusability | ||
| - Clear documentation | ||
| - Safe defaults | ||
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| # Language-specific settings | ||
| language_settings: | ||
| shell: | ||
| # Enable ShellCheck-style analysis | ||
| enable_static_analysis: true | ||
| # Focus on common shell pitfalls | ||
| focus_areas: | ||
| - "error_handling" | ||
| - "variable_quoting" | ||
| - "parameter_expansion" | ||
| - "security" | ||
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| # Exclude certain files from review | ||
| exclude_paths: | ||
| - ".agent/tmp/*" | ||
| - ".agent/memory/*" | ||
| - "*.log" | ||
| - "*.tmp" | ||
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| # Enable specific review features | ||
| features: | ||
| # Enable security-focused reviews | ||
| security_review: true | ||
| # Enable performance analysis | ||
| performance_review: true | ||
| # Enable best practices checking | ||
| best_practices: true | ||
| # Enable documentation review | ||
| documentation_review: true |
There was a problem hiding this comment.
🛠️ Refactor suggestion | 🟠 Major
Restructure configuration for schema compliance. The file requires restructuring to align with CodeRabbit's YAML schema. Key issues: (1) request_changes_workflow must be boolean, (2) language_settings should be removed (use tools.shellcheck), (3) exclude_paths should be path_filters under reviews, (4) features is non-standard and should be removed.
Here's a corrected and simplified configuration that aligns with the schema:
# CodeRabbit Configuration for AI-Assisted DevOps Framework
# https://docs.coderabbit.ai/guides/review-instructions
reviews:
# High-level review focus areas
high_level_summary: true
# Specific areas of focus for this DevOps framework
review_instructions: |
This is an AI-Assisted DevOps Framework with comprehensive automation tools.
Please focus on:
**Shell Script Quality:**
- Proper error handling and return statements
- Consistent variable naming and local variable usage
- Security best practices (no hardcoded credentials)
- Proper quoting and parameter expansion
- ShellCheck compliance
**Architecture & Design:**
- Modular design and separation of concerns
- Consistent patterns across provider helpers
- Clear function responsibilities
- Proper abstraction levels
**Documentation & Maintainability:**
- Clear function and script documentation
- Consistent coding style
- Meaningful variable and function names
- Proper commenting for complex logic
**Security & Best Practices:**
- No sensitive data in code
- Proper input validation
- Safe file operations
- Secure API interactions
**DevOps Automation:**
- Quality assurance automation
- CI/CD pipeline effectiveness
- Multi-platform compatibility
- Error handling in automation scripts
# Keep manual review for this critical framework
auto_approve: false
# Request changes for critical issues
request_changes_workflow: true
# Exclude certain files from review
path_filters:
- "!.agent/tmp/**"
- "!.agent/memory/**"
- "!*.log"
- "!*.tmp"
# Path-specific instructions
path_instructions:
- path: "providers/*.sh"
instructions: |
Provider helper scripts - focus on:
- Consistent API patterns
- Proper error handling
- Security of credential handling
- Input validation
- path: ".agent/scripts/*.sh"
instructions: |
Automation scripts - focus on:
- Reliability and robustness
- Clear logging and feedback
- Proper exit codes
- Error recovery mechanisms
- path: "templates/*.sh"
instructions: |
Template scripts - focus on:
- Security (prompt injection protection)
- Flexibility and reusability
- Clear documentation
- Safe defaults
# Enable specific analysis tools
tools:
shellcheck:
enabled: true🤖 Prompt for AI Agents
In .coderabbit.yaml lines 1-108: convert request_changes_workflow from an object
to a boolean (e.g., request_changes_workflow: true), remove the
language_settings block and instead add tools.shellcheck: enabled: true under
top-level tools, move exclude_paths into reviews.path_filters (use
repository-style globs like "!.agent/tmp/**", "!.agent/memory/**", "!*.log",
"!*.tmp"), and remove the non-standard features section; ensure the rest of the
reviews and path_instructions remain under reviews.
| request_changes_workflow: | ||
| enabled: true |
There was a problem hiding this comment.
Critical schema validation error: request_changes_workflow structure. According to the CodeRabbit schema, request_changes_workflow must be a boolean value, not an object with an enabled property. The current nested structure will cause configuration parsing to fail.
Apply this fix:
# Request changes for critical issues
- request_changes_workflow:
- enabled: true
+ request_changes_workflow: true📝 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.
| request_changes_workflow: | |
| enabled: true | |
| request_changes_workflow: true |
🤖 Prompt for AI Agents
In .coderabbit.yaml around lines 51 to 52, request_changes_workflow is currently
defined as an object with an enabled property which violates the schema; replace
the object with a plain boolean by removing the nested enabled key and setting
request_changes_workflow: true (or false if you want it disabled) so the value
is a top-level boolean as required.
| language_settings: | ||
| shell: | ||
| # Enable ShellCheck-style analysis | ||
| enable_static_analysis: true | ||
| # Focus on common shell pitfalls | ||
| focus_areas: | ||
| - "error_handling" | ||
| - "variable_quoting" | ||
| - "parameter_expansion" | ||
| - "security" |
There was a problem hiding this comment.
Non-standard configuration keys not in CodeRabbit schema. Lines 81-90 define language_settings and shell sections that don't exist in the CodeRabbit configuration schema. To enable ShellCheck-style analysis, use the tools.shellcheck configuration instead.
Replace this section with schema-compliant configuration:
-# Language-specific settings
-language_settings:
- shell:
- # Enable ShellCheck-style analysis
- enable_static_analysis: true
- # Focus on common shell pitfalls
- focus_areas:
- - "error_handling"
- - "variable_quoting"
- - "parameter_expansion"
- - "security"
+# Enable static analysis tools
+tools:
+ shellcheck:
+ enabled: trueCommittable suggestion skipped: line range outside the PR's diff.
🤖 Prompt for AI Agents
In .coderabbit.yaml around lines 81 to 90, remove the non-standard
language_settings -> shell block and replace it with a schema-compliant
tools.shellcheck section; specifically add a tools.shellcheck: enabled: true
entry and move your analysis preferences into that section (for example as a
checks or args list — e.g. focus areas like error_handling, variable_quoting,
parameter_expansion, security should be expressed under tools.shellcheck as a
checks/args array consistent with the CodeRabbit schema). Ensure no leftover
language_settings.shell keys remain.
| exclude_paths: | ||
| - ".agent/tmp/*" | ||
| - ".agent/memory/*" | ||
| - "*.log" | ||
| - "*.tmp" |
There was a problem hiding this comment.
Invalid key exclude_paths — use path_filters instead. The configuration uses exclude_paths which is not recognized by CodeRabbit's schema. The correct key is path_filters (under reviews), which supports both inclusion and exclusion patterns using glob syntax with ! prefix for negation.
Replace this section:
-# Exclude certain files from review
-exclude_paths:
- - ".agent/tmp/*"
- - ".agent/memory/*"
- - "*.log"
- - "*.tmp"
+# Exclude certain files from review (under reviews section)
+ path_filters:
+ - "!.agent/tmp/**"
+ - "!.agent/memory/**"
+ - "!*.log"
+ - "!*.tmp"Note: Move this inside the reviews: block (before line 5 or after request_changes_workflow).
Committable suggestion skipped: line range outside the PR's diff.
🤖 Prompt for AI Agents
.coderabbit.yaml lines 93-97: the file uses an invalid top-level key
`exclude_paths`; move these patterns into the `reviews:` block as `path_filters`
and convert exclusion entries to negated globs (prefix with `!`). Replace the
`exclude_paths` block with a `path_filters:` list inside `reviews:` (place
before line 5 or after `request_changes_workflow`) and change each pattern like
".agent/tmp/*" to a negated entry "! .agent/tmp/*" (and similarly for
".agent/memory/*", "*.log", "*.tmp") so the schema-recognized `path_filters`
handles exclusions correctly.
| features: | ||
| # Enable security-focused reviews | ||
| security_review: true | ||
| # Enable performance analysis | ||
| performance_review: true | ||
| # Enable best practices checking | ||
| best_practices: true | ||
| # Enable documentation review | ||
| documentation_review: true |
There was a problem hiding this comment.
Non-standard features section not in schema. Lines 100-108 define a features section with security_review, performance_review, etc., which don't correspond to CodeRabbit's configuration schema. These review features are controlled by the tools section and individual review settings.
Remove this section and rely on CodeRabbit's default tooling. If you need specific review features, configure them under tools (e.g., tools.semgrep, tools.gitleaks for security) or enable built-in features like pre_merge_checks. The current features block will be silently ignored.
-# Enable specific review features
-features:
- # Enable security-focused reviews
- security_review: true
- # Enable performance analysis
- performance_review: true
- # Enable best practices checking
- best_practices: true
- # Enable documentation review
- documentation_review: true📝 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.
| features: | |
| # Enable security-focused reviews | |
| security_review: true | |
| # Enable performance analysis | |
| performance_review: true | |
| # Enable best practices checking | |
| best_practices: true | |
| # Enable documentation review | |
| documentation_review: true |
🤖 Prompt for AI Agents
.coderabbit.yaml around lines 100 to 108: the file contains a non-standard
top-level features section (security_review, performance_review, best_practices,
documentation_review) that is not part of CodeRabbit's schema and will be
ignored; remove the entire features block and instead configure desired checks
under the tools section (for example enable security scanners with tools.semgrep
or tools.gitleaks, enable performance or best-practices tooling via their
respective tool entries, or enable built-in toggles like pre_merge_checks) so
the configuration uses supported keys and has effect.
✅ COMPREHENSIVE CLI INTEGRATION: - Added complete CodeRabbit CLI wrapper script (.agent/scripts/coderabbit-cli.sh) - Secure API key management with local-only storage - Full command suite: install, setup, review, analyze, status, help - Proper error handling and user-friendly output ✅ WORKFLOW INTEGRATION: - Integrated into quality-check.sh for comprehensive analysis - Added to pre-commit-hook.sh for automated reviews - Updated setup.sh with CodeRabbit CLI installation steps - Enhanced AGENTS.md with detailed usage instructions ✅ SECURITY & BEST PRACTICES: - API key stored securely in ~/.config/coderabbit/api_key (600 permissions) - No API keys committed to repository (placeholder-only approach) - Clear documentation for API key acquisition and setup - Local-only configuration with organization-level access ✅ DOCUMENTATION UPDATES: - Added CodeRabbit badge to README.md - Updated quality metrics to reflect zero technical debt achievement - Comprehensive CLI usage examples in AGENTS.md - Integration instructions in setup workflow ✅ MULTI-PLATFORM QUALITY ASSURANCE: - SonarCloud: Zero issues (100% resolution) - CodeFactor: A- rating maintained - CodeRabbit: AI-powered review integration ready - Comprehensive quality pipeline with automated checks 🎯 ACHIEVEMENT: Complete AI-powered code review integration 🔧 TOOLS: CLI automation + secure API key management 🚀 WORKFLOW: Seamless integration into existing DevOps pipeline 🔒 SECURITY: Zero API keys in repository, local-only configuration
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- Add yaml-language-server schema reference - Move path_instructions under reviews (was at root level) - Change path_filters from object to array of strings with ! prefix - Move review_instructions to tone_instructions (correct field name) - Add TypeScript path instructions Addresses feedback from PR #1, #3, #5 about unrecognized properties
- Fix model priority: Nano Banana Pro (Gemini 3.0) promoted to #1 from #6 Based on Higgsfield's own docs: native 4K, best text rendering, <10s generation - Add REST API client for cloud.higgsfield.ai (separate credit pool from web UI) - apiGenerateImage(): text-to-image via API with polling and auto-download - apiGenerateVideo(): image-to-video via API with file upload support - apiUploadFile(): pre-signed URL upload for local images/videos - apiPollStatus(): exponential backoff polling matching Python SDK pattern - apiStatus(): credential validation and connectivity check - apiRequest(): authenticated fetch with retry on transient errors (408/429/5xx) - Add --api flag: route image/video through REST API with Playwright fallback - Add --api-only flag: API-only mode, fail without fallback - Add api-status command: verify API credentials and connectivity - Add 17 API model ID mappings (7 image, 8 video, 1 edit, 1 reference) - Fix pre-existing syntax error: missing closing brace for batchLipsync() - Self-tests: 78 passing (up from 44), covering all new API logic
* feat: add Higgsfield Cloud API client and fix model priority ranking - Fix model priority: Nano Banana Pro (Gemini 3.0) promoted to #1 from #6 Based on Higgsfield's own docs: native 4K, best text rendering, <10s generation - Add REST API client for cloud.higgsfield.ai (separate credit pool from web UI) - apiGenerateImage(): text-to-image via API with polling and auto-download - apiGenerateVideo(): image-to-video via API with file upload support - apiUploadFile(): pre-signed URL upload for local images/videos - apiPollStatus(): exponential backoff polling matching Python SDK pattern - apiStatus(): credential validation and connectivity check - apiRequest(): authenticated fetch with retry on transient errors (408/429/5xx) - Add --api flag: route image/video through REST API with Playwright fallback - Add --api-only flag: API-only mode, fail without fallback - Add api-status command: verify API credentials and connectivity - Add 17 API model ID mappings (7 image, 8 video, 1 edit, 1 reference) - Fix pre-existing syntax error: missing closing brace for batchLipsync() - Self-tests: 78 passing (up from 44), covering all new API logic * refactor: extract API helpers to reduce cyclomatic complexity Extract shared logic from apiGenerateImage/apiGenerateVideo into: - apiSubmitAndPoll(): submit + poll pattern - apiDownloadImages(): image download + sidecar - apiDownloadVideo(): video download + sidecar - requireApiCredentials(): credential validation - logApiPrompt(): truncated prompt logging Addresses CodeFactor 'Complex Method' notices.
…oning engine (t1118) The supervisor AI couldn't diagnose its own failures because it never saw its action execution results. This adds: 1. Section 10 in ai-context.sh (build_self_reflection_context): - Execution summary across last 5 cycles (executed/failed/skipped rates) - Recurring skip reasons with counts (reveals prompt/validator mismatches) - Recurring failures with counts - Action repetition detection (same targets across cycles) - Pipeline errors from ai-supervisor.log 2. Analysis area #9 in reasoning prompt (ai-reason.sh): - Instructs AI to review self-reflection data and create improvement tasks for its own recurring failures 3. Added adjust_priority example to output format: - The AI kept omitting new_priority because no example showed the field - This was the #1 skip reason (10 skips across 5 cycles) The AI can now self-diagnose issues like: - 'adjust_priority skipped 10x: missing new_priority' -> fix own output - 'create_improvement skipped 6x: invalid type' -> flag deployment gap - 'issue #1601 acted on 3x across 5 cycles' -> stop repeating - 'jq compile errors in pipeline' -> create fix task
…ts own failures (#1671) * chore: regenerate MODELS.md leaderboard (t1012) * feat: add AI self-reflection context — feed execution history to reasoning engine (t1118) The supervisor AI couldn't diagnose its own failures because it never saw its action execution results. This adds: 1. Section 10 in ai-context.sh (build_self_reflection_context): - Execution summary across last 5 cycles (executed/failed/skipped rates) - Recurring skip reasons with counts (reveals prompt/validator mismatches) - Recurring failures with counts - Action repetition detection (same targets across cycles) - Pipeline errors from ai-supervisor.log 2. Analysis area #9 in reasoning prompt (ai-reason.sh): - Instructs AI to review self-reflection data and create improvement tasks for its own recurring failures 3. Added adjust_priority example to output format: - The AI kept omitting new_priority because no example showed the field - This was the #1 skip reason (10 skips across 5 cycles) The AI can now self-diagnose issues like: - 'adjust_priority skipped 10x: missing new_priority' -> fix own output - 'create_improvement skipped 6x: invalid type' -> flag deployment gap - 'issue #1601 acted on 3x across 5 cycles' -> stop repeating - 'jq compile errors in pipeline' -> create fix task
…al checkpoint (t1256) Root cause analysis of 114 Phase 0.7 recovery events (30 days): - worker_rate_limited: 33 events (29%) — immediate re-dispatch into same rate limit - eval_process_died: 30 events (26%) — pulse killed mid-evaluation, imprecise diagnosis - worker_failed_before_eval: 27 events (24%) — worker crashes before evaluation - worker_oom_killed: 12 events (11%) — OOM kills Fixes: 1. Rate limit cooldown (t1256): Phase 0.7 now sets rate_limit_until = now+5min when recovering a worker_rate_limited task. cmd_next() skips tasks until cooldown expires, preventing immediate re-dispatch into the same rate limit. Addresses #1 root cause. Configurable via SUPERVISOR_RATE_LIMIT_COOLDOWN_SECONDS (default: 300s). 2. Eval checkpoint file (t1256): evaluate_with_ai() writes a checkpoint file at eval start, removed on completion. If the pulse is killed mid-eval, the checkpoint persists. _diagnose_stale_root_cause() now detects 'pulse_killed_mid_eval' vs the generic 'eval_process_died', enabling more precise observability. 3. DB schema: Added rate_limit_until column to tasks table (migration + schema). 4. Stale GC report: Added rate limit cooldown section showing currently deferred tasks.
…al checkpoint (t1256) (#1963) Root cause analysis of 114 Phase 0.7 recovery events (30 days): - worker_rate_limited: 33 events (29%) — immediate re-dispatch into same rate limit - eval_process_died: 30 events (26%) — pulse killed mid-evaluation, imprecise diagnosis - worker_failed_before_eval: 27 events (24%) — worker crashes before evaluation - worker_oom_killed: 12 events (11%) — OOM kills Fixes: 1. Rate limit cooldown (t1256): Phase 0.7 now sets rate_limit_until = now+5min when recovering a worker_rate_limited task. cmd_next() skips tasks until cooldown expires, preventing immediate re-dispatch into the same rate limit. Addresses #1 root cause. Configurable via SUPERVISOR_RATE_LIMIT_COOLDOWN_SECONDS (default: 300s). 2. Eval checkpoint file (t1256): evaluate_with_ai() writes a checkpoint file at eval start, removed on completion. If the pulse is killed mid-eval, the checkpoint persists. _diagnose_stale_root_cause() now detects 'pulse_killed_mid_eval' vs the generic 'eval_process_died', enabling more precise observability. 3. DB schema: Added rate_limit_until column to tasks table (migration + schema). 4. Stale GC report: Added rate limit cooldown section showing currently deferred tasks.
…t1258) Three bugs causing 100% of tasks to route through Phase 0.7 stale recovery instead of completing normally: 1. Check ordering bug: worker_failed_before_eval fired BEFORE the heartbeat check in _diagnose_stale_root_cause(). Tasks actively evaluating (heartbeat fresh) were incorrectly recovered if their log contained WORKER_FAILED from a previous retry's REPROMPT METADATA header. Fix: move heartbeat check first. 2. Wrong log file for ai_eval_timeout: the check searched the worker log for 'evaluate_with_ai' — a supervisor function that never appears in worker logs. This check never matched, masking ai_eval_timeout diagnoses. Fix: search the supervisor log (SUPERVISOR_LOG) instead, scoped to the task ID. 3. Log tail scope for worker_failed_before_eval: full-log grep caused false positives from REPROMPT METADATA headers embedding previous failure content. Fix: only check last 20 lines (actual execution status, not embedded history). 4. Phase 0.7 recovery routing: running tasks with a PR URL were re-queued unnecessarily (e.g., worker_oom_killed after creating PR). Fix: extend the evaluating+PR fast-path to all states — any stale task with a PR routes to pr_review regardless of whether it was in running or evaluating state. Root cause data (last 2 days, 124 events): worker_rate_limited: 38 (30.6%) — rate limit cooldown already handles eval_process_died: 30 (24.2%) — fix #1 prevents false recoveries worker_failed_before_eval: 30 (24.2%) — fix #1+#3 prevent false positives worker_oom_killed: 13 (10.5%) — fix #4 routes to pr_review when PR exists pulse_killed_after_pr_persist: 8 (6.5%) — already handled by fast-path ai_eval_timeout: 3 (2.4%) — fix #2 enables correct diagnosis
…t1258) (#1966) Three bugs causing 100% of tasks to route through Phase 0.7 stale recovery instead of completing normally: 1. Check ordering bug: worker_failed_before_eval fired BEFORE the heartbeat check in _diagnose_stale_root_cause(). Tasks actively evaluating (heartbeat fresh) were incorrectly recovered if their log contained WORKER_FAILED from a previous retry's REPROMPT METADATA header. Fix: move heartbeat check first. 2. Wrong log file for ai_eval_timeout: the check searched the worker log for 'evaluate_with_ai' — a supervisor function that never appears in worker logs. This check never matched, masking ai_eval_timeout diagnoses. Fix: search the supervisor log (SUPERVISOR_LOG) instead, scoped to the task ID. 3. Log tail scope for worker_failed_before_eval: full-log grep caused false positives from REPROMPT METADATA headers embedding previous failure content. Fix: only check last 20 lines (actual execution status, not embedded history). 4. Phase 0.7 recovery routing: running tasks with a PR URL were re-queued unnecessarily (e.g., worker_oom_killed after creating PR). Fix: extend the evaluating+PR fast-path to all states — any stale task with a PR routes to pr_review regardless of whether it was in running or evaluating state. Root cause data (last 2 days, 124 events): worker_rate_limited: 38 (30.6%) — rate limit cooldown already handles eval_process_died: 30 (24.2%) — fix #1 prevents false recoveries worker_failed_before_eval: 30 (24.2%) — fix #1+#3 prevent false positives worker_oom_killed: 13 (10.5%) — fix #4 routes to pr_review when PR exists pulse_killed_after_pr_persist: 8 (6.5%) — already handled by fast-path ai_eval_timeout: 3 (2.4%) — fix #2 enables correct diagnosis
Flagged for Human ReviewReason: t011 (Evaluate Tambo AI generative UI SDK) has ~8h estimate with no subtasks and is not registered in supervisor DB (cross-repo collision risk). Needs manual DB registration before subtasking, or manual breakdown by @marcus. Cannot safely create_subtasks without DB entry. This issue has been flagged by the AI supervisor for human review. Please assess and take appropriate action. Flagged by AI Supervisor (automated reasoning cycle) |
Flagged for Human ReviewReason: a managed private repo t011 (Evaluate Tambo AI generative UI SDK) has ~8h estimate with no subtasks and is not registered in supervisor DB — cannot safely create subtasks due to cross-repo collision risk. Human should either: (1) register t011 in supervisor DB via claim-task-id.sh, then break into subtasks, or (2) manually add subtasks to a managed private repo TODO.md with safe IDs. This issue has been flagged by the AI supervisor for human review. Please assess and take appropriate action. Flagged by AI Supervisor (automated reasoning cycle) |
Flagged for Human ReviewReason: t011 (a managed private repo) has ~8h estimate exceeding auto-dispatch threshold but is marked 'not-in-db' — cannot safely create subtasks due to cross-repo collision risk. Human needs to register this task in supervisor DB before it can be broken down and dispatched. This issue has been flagged by the AI supervisor for human review. Please assess and take appropriate action. Flagged by AI Supervisor (automated reasoning cycle) |
Flagged for Human ReviewReason: t011 (a managed private repo) has ~8h estimate with no subtasks and is flagged 'not-in-db' — cannot safely create subtasks due to cross-repo collision risk. Needs manual registration in supervisor DB before it can be broken down and dispatched. This issue has been flagged by the AI supervisor for human review. Please assess and take appropriate action. Flagged by AI Supervisor (automated reasoning cycle) |
Flagged for Human ReviewReason: t1311 has malformed blocked-by field (blocked-by:`) — dependency cannot be resolved. Needs manual correction in TODO.md to either remove the blocker or specify the correct task ID. This issue has been flagged by the AI supervisor for human review. Please assess and take appropriate action. Flagged by AI Supervisor (automated reasoning cycle) |
Flagged for Human ReviewReason: a managed private repo t011 (Evaluate Tambo AI generative UI SDK) has estimate >4h and needs subtasking, but is flagged as 'not-in-db: task not registered in supervisor DB — cannot create subtasks safely (cross-repo collision risk)'. Human needs to register this task in the supervisor DB before it can be broken down and dispatched. Current estimate is ~8h with no subtasks. This issue has been flagged by the AI supervisor for human review. Please assess and take appropriate action. Flagged by AI Supervisor (automated reasoning cycle) |
Flagged for Human ReviewReason: a managed private repo t011 (Evaluate Tambo AI generative UI SDK) needs subtasking (~8h estimate, no subtasks) but is flagged as not-in-db with cross-repo collision risk. Human action needed: register t011 in supervisor DB for a managed private repo repo before subtasks can be safely created. After registration, break into 2-3 subtasks (~2-4h each) for auto-dispatch. This issue has been flagged by the AI supervisor for human review. Please assess and take appropriate action. Flagged by AI Supervisor (automated reasoning cycle) |
Flagged for Human ReviewReason: Task t1311 has a malformed blocked-by dependency (blocked-by:` — literal backtick). This prevents dispatch despite being marked eligible. A human should edit TODO.md to either remove the invalid blocker or set the correct dependency. This issue has been flagged by the AI supervisor for human review. Please assess and take appropriate action. Flagged by AI Supervisor (automated reasoning cycle) |
Flagged for Human ReviewReason: 4 medium-severity audit findings (3 closed_issue_audit + 1 orphan_pr_audit) need human review. The audit details are not included in the snapshot, so the specific issues/PRs cannot be identified programmatically. Run This issue has been flagged by the AI supervisor for human review. Please assess and take appropriate action. Flagged by AI Supervisor (automated reasoning cycle) |
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