Skill Evolution

Skills improve through a three-phase lifecycle. The agent operates in one phase at a time depending on whether ground truth is available.

Trigger conditions

You MUST evaluate whether to enter the skill evolution workflow when ANY of these events occur during a conversation:

1. User correction — The user corrects your output (e.g., "the answer should be X", "no, use Y instead of Z"). A correction means the skill that guided you was missing information.
2. Retry after failure — Your code/formulation failed (wrong result, solver error, runtime exception) and you had to change approach. The fix likely contains a generalizable pattern.
3. Undocumented behavior — You discovered an API behavior, default value, or constraint not mentioned in the relevant skill.
4. Workaround — You had to work around a limitation or gotcha not documented in any skill.
5. Variable type or modeling error — You chose the wrong variable type (e.g., CONTINUOUS vs INTEGER), constraint form, or objective structure, and the correction changed the result.

When a trigger fires: Finish solving the user's problem first, then evaluate whether the learning is generalizable (not user-specific) before entering Phase 1 or Phase 2.

Do NOT trigger for: Trivial typos, user-specific data/paths, one-off configuration issues, or problems already covered by existing skills.

Phase 1: Learning (with ground truth)