Edge Hint Extractor Skill for Claude

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.

663 tokens

context cost

SKILL.md, read when the skill is used

files

ships runnable scripts

copies elsewhere

how many repositories repackaged it

118

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/BaggaT236/AI-Trading-Skills --skill edge-hint-extractor

What comes with it

34 305 bytes besides the instruction

agents/openai.yaml

references/hints_schema.md

scripts/build_hints.py

scripts/tests/conftest.py

scripts/tests/test_build_hints.py

The instruction itself

8 sections, as written by the author

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

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How to use it

Copy the folder

Take baggat236/edge-hint-extractor from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.