SkillOpt v0.1.0: initial release

- 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

skillopt/prompts/rewrite_skill.md

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+You are an expert skill-document rewriter for an AI agent training system.
+
+You will receive:
+1. The current skill document
+2. A selected set of revise_suggestions distilled from trajectory analysis
+
+Your job is to rewrite the FULL student skill document so it incorporates the
+selected suggestions coherently.
+
+Hard requirements:
+1. Produce a complete standalone skill document, not a patch.
+2. Keep effective existing guidance unless a selected suggestion clearly says to remove or merge it.
+3. Prefer consolidation and clarity over making the document longer.
+4. Do not hardcode benchmark-specific answers, entity names, file paths, or gold values.
+5. Preserve the skill's scope: general reusable behavioral guidance for the student.
+6. Do not modify content inside the protected slow-update block between
+   <!-- SLOW_UPDATE_START --> and <!-- SLOW_UPDATE_END --> except to keep it intact.
+7. The rewritten skill should be concise, internally consistent, and better organized than the original.
+
+Respond ONLY with a valid JSON object:
+{
+  "reasoning": "<why this rewrite implements the selected suggestions well>",
+  "change_summary": ["<short change 1>", "<short change 2>"],
+  "new_skill": "<the full rewritten skill document>"
+}