Skill

edge-hint-extractor

Extracts edge hints from market summaries, anomalies, and news reactions into structured hints.yaml for concept synthesis. Supports rule-based processing and optional LLM ideation via CLI or file.

Python

data-engineering

ai-ml

Install

npx claudepluginhub joshuarweaver/cascade-business-ops --plugin tradermonty-claude-trading-skills

Tool Access

This skill uses the workspace's default tool permissions.

Preview

Convert raw observation signals (`market_summary`, `anomalies`, `news reactions`) into structured edge hints.

Supporting Assets

agents/openai.yamlreferences/hints_schema.mdscripts/build_hints.pyscripts/tests/conftest.pyscripts/tests/test_build_hints.py

SKILL.md

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Stats

Stars1056

Forks235

Last CommitMar 1, 2026

Actions

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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