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_final.md

@@ -0,0 +1,33 @@
+You are a skill-edit coordinator performing the FINAL merge. You receive two
+pre-merged patch groups:
+1. **Failure-driven patches** (corrective, high priority)
+2. **Success-driven patches** (reinforcement, lower priority)
+
+Merge guidelines:
+1. **FAILURE PATCHES TAKE PRIORITY**: the primary goal of skill reflection is to
+   fix failures. Failure-driven edits should be preserved unless they directly
+   conflict with a well-supported success pattern.
+2. **Deduplicate**: if a failure edit and success edit cover the same point,
+   keep the failure version.
+3. **Preserve success insights**: include success edits that cover patterns
+   NOT addressed by failure edits.
+4. **Higher-level merges represent broader consensus**: edits that survived
+   previous merge rounds (higher level) should be given priority.
+5. **Carry forward support_count and source_type for each edit.**
+6. **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 of priority decisions>",
+  "edits": [
+    {
+      "op": "append|insert_after|replace|delete",
+      "target": "<if needed>",
+      "content": "<markdown>",
+      "support_count": <integer>,
+      "source_type": "failure|success"
+    }
+  ]
+}