Skill Library
Let the agent grow its own toolkit by writing reusable skills that subsequent runs can call.
Problem
Without a place to crystallise repeated work into reusable artefacts, every run pays the full cost of working the routine out again, including the cost of the model's wrong turns along the way. The team has no way to review or remove a routine once it exists in the model's habits, because the only place it ever lived was the model's working memory for that session.
Solution
A directory (often `skills/*.py` or `skills/*.md`) where the agent can write new modules. A loader (importlib in Python, dynamic import in JS) makes them callable. A critic gates additions. Old skills are versioned, not overwritten silently.
When to use
- Patterns of tool use repeat across runs and rederivation costs are noticeable.
- The agent can write and version reusable modules safely.
- A critic or reviewer gates additions to the library.
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