tradermonty/claude-trading-skills

trade-hypothesis-ideator

Generate falsifiable trade strategy hypotheses from market data, trade logs, and journal snippets.

Quelltext ansehen

Verwendung

  1. Installationsbefehl kopieren und das Quellpaket vor der Installation in der eigenen Agentenumgebung prüfen.
  2. Benötigte Werkzeuge, Zugangsdaten und Hosts im Original prüfen.
  3. Eingabe und gewünschtes Ergebnis beschreiben und die Ausgabe mit den Quellen abgleichen.
npx skills add https://github.com/tradermonty/claude-trading-skills --skill trade-hypothesis-ideator

Vor dem Start

  • Die Installation umfasst weder Modellabo noch API-Kontingent oder Dateizugriffsrechte.
  • Sterne und Installationen zeigen Aktivität, keine unabhängige Qualitäts- oder Sicherheitsprüfung.
Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

Trade Hypothesis Ideator

Generate 1-5 structured hypothesis cards from a normalized input bundle, critique and rank them, then optionally export pursue cards into strategy.yaml + metadata.json artifacts.

When to Use

  • After gathering trade logs, journal entries, or market observations that suggest a potential edge
  • When you have a structured input bundle (JSON) with evidence snippets and want falsifiable hypotheses
  • To bridge qualitative observations into quantitative experiment designs
  • Before committing capital to validate a new strategy idea with kill criteria

Prerequisites

  • Input JSON bundle with one or more of: trade_log, journal_snippets, market_data, observations
  • Python 3.9+ with pyyaml installed
  • No external API keys required (pure calculation skill)

Workflow

  1. Receive input JSON bundle.
  2. Run pass 1 normalization + evidence extraction.
  3. Generate hypotheses with prompts:
  • prompts/system_prompt.md
  • prompts/developer_prompt_template.md (inject {{evidence_summary}})
  1. Critique hypotheses with prompts/critique_prompt_template.md.
  2. Run pass 2 ranking + output formatting + guardrails.
  3. Optionally export pursue hypotheses via Step H strategy exporter.

Scripts

  • Pass 1 (evidence summary):
bash
python3 skills/trade-hypothesis-ideator/scripts/run_hypothesis_ideator.py \
  --input skills/trade-hypothesis-ideator/examples/example_input.json \
  --output-dir reports/
  • Pass 2 (rank + output + optional export):
bash
python3 skills/trade-hypothesis-ideator/scripts/run_hypothesis_ideator.py \
  --input skills/trade-hypothesis-ideator/examples/example_input.json \
  --hypotheses reports/raw_hypotheses.json \
  --output-dir reports/ \
  --export-strategies

Output

  • hypothesis_cards_<date>.json — Ranked hypothesis cards with verdicts (pursue, revise, discard)
  • hypothesis_cards_<date>.md — Human-readable summary with experiment designs and kill criteria
  • strategy_<hypothesis_id>.yaml — (Optional) Edge-finder-compatible strategy export for pursue cards
  • metadata_<hypothesis_id>.json — (Optional) Provenance metadata for exported strategies

Resources

  • references/hypothesis_types.md — Taxonomy of hypothesis patterns (mean-reversion, momentum, event-driven, etc.)
  • references/evidence_quality_guide.md — Criteria for rating evidence strength and sample size requirements

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