Edge Hint Extractor Overview Convert raw observation signals ( market_summary , anomalies , news reactions ) into structured edge hints. This skill is the first stage in the split workflow: observe -> abstract -> design -> pipeline . When to Use You want to turn daily market observations into reusable hint objects. You want LLM-generated ideas constrained by current anomalies/news context. You need a clean hints.yaml input for concept synthesis or auto detection. Prerequisites Python 3.9+ PyYAML Optional inputs from detector run: market_summary.json anomalies.json news_reactions.csv or news_reactions.json Output hints.yaml containing: hints list generation metadata rule/LLM hint counts Workflow Gather observation files ( market_summary , anomalies , optional news reactions). Run scripts/build_hints.py to generate deterministic hints. Optionally augment hints with LLM ideas via one of two methods: a. --llm-ideas-cmd — pipe data to an external LLM CLI (subprocess). b. --llm-ideas-file PATH — load pre-written hints from a YAML file (for Claude Code workflows where Claude generates hints itself). Pass hints.yaml into concept synthesis or auto detection. Note: --llm-ideas-cmd and --llm-ideas-file are mutually exclusive. Quick Commands Rule-based only (default output to reports/edge_hint_extractor/hints.yaml ): python3 skills/edge-hint-extractor/scripts/build_hints.py \ --market-summary /tmp/edge-auto/market_summary.json \ --anomalies /tmp/edge-auto/anomalies.json \ --news-reactions /tmp/news_reactions.csv \ --as-of 2026 -02-20 \ --output-dir reports/ Rule + LLM augmentation (external CLI): python3 skills/edge-hint-extractor/scripts/build_hints.py \ --market-summary /tmp/edge-auto/market_summary.json \ --anomalies /tmp/edge-auto/anomalies.json \ --llm-ideas-cmd "python3 /path/to/llm_ideas_cli.py" \ --output-dir reports/ Rule + LLM augmentation (pre-written file, for Claude Code): python3 skills/edge-hint-extractor/scripts/build_hints.py \ --market-summary /tmp/edge-auto/market_summary.json \ --anomalies /tmp/edge-auto/anomalies.json \ --llm-ideas-file /tmp/llm_hints.yaml \ --output-dir reports/ Resources skills/edge-hint-extractor/scripts/build_hints.py references/hints_schema.md

安装