tradermonty/claude-trading-skills741 installs

edge-hint-extractor

Q: How do I install this agent skill?

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

Q: Is this agent skill safe to install?

Review the displayed partner audits, complete source, permissions, dependencies, and exact revision before installing.

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.

How do I install this agent skill?

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

view source ↗

Is this agent skill safe to install?

Gen Agent Trust Hubwarn
The edge-hint-extractor skill allows for arbitrary shell command execution via a configuration parameter, which could be exploited if an agent is manipulated into running a malicious command string. It also processes untrusted external market and news data, creating a surface for indirect prompt injection into downstream LLM components.
Socketwarn
1 alert: gptAnomaly
Snykwarn
Risk: MEDIUM · 1 issue
Runlayerpass
2/6 files flagged
ZeroLeakspass
Score: 93/100 · 2 sections analyzed

What does this agent skill do?

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

How can the creator link this skill?

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/tradermonty/claude-trading-skills/edge-hint-extractor">View edge-hint-extractor on skillZs</a>