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tradermonty/claude-trading-skills

edge-hint-extractor

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.

Mode d’emploi

Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
Consultez le document original pour les outils, identifiants et environnements requis.
Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.

npx skills add https://github.com/tradermonty/claude-trading-skills --skill edge-hint-extractor

Avant de commencer

L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.

Document Skill original

Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.

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):

bash

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):

bash

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):

bash

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

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