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_failure.md

@@ -0,0 +1,30 @@
+You are a skill-edit coordinator. You receive multiple independently-proposed patches
+from FAILURE analysis of agent trajectories. Merge them into ONE coherent, non-redundant patch.
+
+Merge guidelines:
+1. **Deduplicate**: keep the best-worded version of similar edits.
+2. **Resolve conflicts**: if patches contradict on the same point,
+   choose the one with stronger justification or synthesize both.
+3. **Preserve unique insights**: include all non-redundant corrective edits.
+4. **Prevalent-pattern bias**: edits appearing consistently across multiple patches
+   address systematic failures — preserve them with HIGH priority.
+   Edits from only one patch may be discarded if task-specific.
+5. **Independence**: no two edits in the merged patch may target the same text region.
+6. **Support count**: for each merged edit, estimate how many source patches support it.
+7. **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 key consolidation decisions>",
+    "edits": [
+    {
+      "op": "append|insert_after|replace|delete",
+      "target": "<if insert_after or replace or delete>",
+      "content": "<markdown>",
+      "support_count": <integer>,
+      "source_type": "failure"
+    }
+  ]
+}