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.

소스 보기

사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/tradermonty/claude-trading-skills --skill edge-hint-extractor

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

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

  1. Gather observation files (market_summary, anomalies, optional news reactions).
  2. Run scripts/build_hints.py to generate deterministic hints.
  3. 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).
  1. 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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