/edge-hint-extractor

name: edge-hint-extractor
description: Extract edge hints from daily market observations and news reactions, with optional LLM ideation, and output canonical hints.yaml for downstream concept synthesis and auto detection.

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

1. Gather observation files (`market_summary`, `anomalies`, optional news reactions). 2. Run `scripts/build_hints.py` to generate deterministic hints. 3. 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).

4. 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`