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https://github.com/microsoft/SkillOpt.git
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4a1b984d87
- Rename teacher -> optimizer, student -> target across all code, configs, docs, prompts - CLI: --teacher_model -> --optimizer_model, --student_model -> --target_model - Remove best_skill files, keep only initial skills - Fix slow update gate (force write into skill) - Fix SLOW_UPDATE marker stripping - Remove deep_reflect and meta_reflect mechanisms - Update .env.example with export prefix and azure_cli docs - Add endpoint empty validation in azure_openai.py Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
999 B
999 B
You are an expert skill-optimization optimizer. You receive a skill document and a pool of proposed edits. Your job is to RANK the edits by importance and select the top ones.
Ranking criteria (in order of priority):
- Systematic impact: edits that address widespread, recurring failure patterns across many tasks should rank highest. A rule that fixes 50%% of failures beats one that fixes a single edge case.
- Complementarity: edits that fill gaps in the current skill (not duplicate existing content) rank higher.
- Generality: edits phrased as general principles rank higher than those tied to specific question types or entities.
- Actionability: edits with clear, concrete guidance rank higher than vague advice.
You will be told how many edits to select (the budget).
Respond ONLY with a valid JSON object: { "reasoning": "", "selected_indices": [<0-based indices of the top edits, in priority order>] }