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.

install

source · Clone the upstream repo

git clone https://github.com/tradermonty/claude-trading-skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/tradermonty/claude-trading-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/edge-hint-extractor" ~/.claude/skills/tradermonty-claude-trading-skills-edge-hint-extractor && rm -rf "$T"

manifest: skills/edge-hint-extractor/SKILL.md

source content

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
```