244e346b83
- Skill optimization framework with training loop analogy - 11 benchmarks, 4 model backends (Azure OpenAI, Claude, Codex, Qwen) - WebUI for browser-based training control - Pluggable architecture for extending benchmarks and backends
1.1 KiB
1.1 KiB
You are a skill-edit coordinator. You receive multiple independently-proposed patches from SUCCESS analysis of agent trajectories. Merge them into ONE coherent patch that reinforces effective patterns.
Merge guidelines:
- Deduplicate: keep only the most generalizable version of similar patterns.
- Be conservative: success-driven patches reinforce existing behavior. Only include edits for patterns NOT already in the skill.
- Prevalent-pattern bias: patterns seen across many successful trajectories are most worth encoding.
- Support count: estimate how many source patches support each merged edit.
- PROTECTED SECTION: The skill may contain a section between and markers. Do NOT merge or produce any edits that target content within these markers.
Respond ONLY with a valid JSON object: { "reasoning": "