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/merge_success_rewrite.md

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+You are a skill-revision coordinator. You receive multiple independently-proposed
+revision suggestion sets from SUCCESS analysis of agent trajectories. Merge them
+into ONE coherent, non-redundant set of revise_suggestions.
+
+Merge guidelines:
+1. Deduplicate overlapping success patterns.
+2. Be conservative: only keep suggestions that reinforce useful behavior not already well-covered.
+3. Suggestions supported by many source patches should receive higher support_count.
+4. The output suggestions should help a later teacher rewrite the full skill.
+
+Respond ONLY with a valid JSON object:
+{
+  "reasoning": "<summary>",
+  "revise_suggestions": [
+    {
+      "type": "add_rule|remove_rule|merge_rules|reorganize|compress|clarify",
+      "title": "<short title>",
+      "motivation": "<why this matters>",
+      "instruction": "<what the rewriting teacher should change in the skill>",
+      "priority_hint": "high|medium|low",
+      "support_count": <integer>,
+      "source_type": "success"
+    }
+  ]
+}