If you’re building agents that interface with the messy real world (GitHub, Asana, Gmail), "vibe coding" a system prompt isn't enough. Seer provides the primitives to move from flaky demos to deterministic, self-healing agents.

Hardcoding 50 tools into a system prompt leads to hallucinations and context-window bloat.

• The Solution: We implement Dynamic Tool Selection at runtime. Your agent only "sees" and "loads" tools relevant to the current execution state, keeping the context lean and performance high.

Context-window pollution is the #1 killer of agent reliability.

• The Problem: One agent trying to do everything eventually loses the thread.
• The Solution: Our supervisor repo implements a Supervisor-Worker pattern. The supervisor manages high-level state and spawns ephemeral sub-agents for specific sub-tasks. This keeps the context for each task surgically clean.

Generating test cases is boring; provisioning environments to run them is worse.

• The Solution: Our Eval Agent handles the "Setup Fatigue." It interviews your code to generate a spec, then automatically provisions sandboxed integrations (GitHub repos, Jira boards, etc.) to run the tests. You provide the goal; Seer provides the environment.

• seer: The core ARE (Autonomous Reliability Engineering) engine.
• supervisor: Logic for spawning sub-agents and maintaining clean context boundaries.
• tool_hub: Runtime discovery and dynamic tool routing.

We use AGPL-3.0. If you run a hosted version of Seer, you must share your modifications.

Contributing requires a Contributor License Agreement (CLA) so we can support teams whose legal policies prevent them from using AGPL directly. See CONTRIBUTING.md for details.