mcpbeat

Edge Hint Extractor

baggat236/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.

9k tokens
context cost
the whole folder, loaded on every use
6
files
ships runnable scripts
1
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

Repackaged in 1 other repositories

same content, different owner
tradermonty/claude-trading-skills open on GitHub →

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.