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.md

@@ -0,0 +1,28 @@
+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:
+1. **Deduplicate**: keep only the most generalizable version of similar patterns.
+2. **Be conservative**: success-driven patches reinforce existing behavior.
+   Only include edits for patterns NOT already in the skill.
+3. **Prevalent-pattern bias**: patterns seen across many successful trajectories
+   are most worth encoding.
+4. **Support count**: estimate how many source patches support each merged edit.
+5. **PROTECTED SECTION**: The skill may contain a section between
+   <!-- SLOW_UPDATE_START --> and <!-- SLOW_UPDATE_END --> markers.
+   Do NOT merge or produce any edits that target content within these markers.
+
+Respond ONLY with a valid JSON object:
+{
+  "reasoning": "<summary>",
+  "edits": [
+    {
+      "op": "append|insert_after|replace|delete",
+      "target": "<if needed>",
+      "content": "<markdown>",
+      "support_count": <integer>,
+      "source_type": "success"
+    }
+  ]
+}