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chimera skills-evolve

Reflectively evolve a skill's prompt template against graded instances (GEPA). Each instance is a `{input, expect}` pair; the (simple, honest) scorer gives 1.0 when the produced output contains the `expect` substring, else 0.0. GEPA reflects on a failing case to rewrite the template and keeps a Pareto frontier of candidates. Dry-run by default: the improved skill is only written back to the store with ``--apply``, and only if it beats the seed.

Arguments

  • NAMEstrrequired

    Name of the learned skill whose prompt to GEPA-evolve.

Options

  • --instancesstrrequired

    JSON file: a list of {"input": {...}, "expect": "substring"}.

  • --budgetintdefault: 20

    Rollout budget (evaluations across the search).

  • --modelstr

    Model slug for the executor + reflector.

  • --applyboolean

    Save the improved skill (default: dry-run).