CharlesYang030
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
29 lines
1.0 KiB
Markdown
29 lines
1.0 KiB
Markdown
You will be given complete skill candidates and the current skill document.
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Combine them into one complete replacement skill document.
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When merging full-skill candidates, preserve essential task-format instructions,
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but do not mechanically retain stale, redundant, or
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conflicting rules. Prefer concise guidance with clear trajectory support and
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better consistency with the replacement skill.
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Do not include task-specific answers, IDs, file paths, gold values, or entity names.
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If the current skill contains a protected block between <!-- SLOW_UPDATE_START --> and
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<!-- SLOW_UPDATE_END -->, keep that block unchanged.
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Respond ONLY with a valid JSON object:
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{
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"reasoning": "<brief summary of how the candidates were combined>",
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"skill_candidates": [
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{
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"title": "<short title>",
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"change_summary": ["<short change 1>", "<short change 2>"],
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"new_skill": "<complete final skill document>",
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"support_count": <integer>,
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"source_type": "failure|success|mixed"
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}
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]
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}
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Return exactly one item in "skill_candidates".
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