CtrlK
BlogDocsLog inGet started
Tessl Logo

trade-hypothesis-ideator

Generate falsifiable trade strategy hypotheses from market data, trade logs, and journal snippets. Use when you have a structured input bundle and want ranked hypothesis cards with experiment designs, kill criteria, and optional strategy.yaml export compatible with edge-finder-candidate/v1.

64

Quality

75%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/trade-hypothesis-ideator/SKILL.md
SKILL.md
Quality
Evals
Security

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}})
  4. Critique hypotheses with prompts/critique_prompt_template.md.
  5. Run pass 2 ranking + output formatting + guardrails.
  6. Optionally export pursue hypotheses via Step H strategy exporter.

Scripts

  • Pass 1 (evidence summary):
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):
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
Repository
tradermonty/claude-trading-skills
Last updated
First committed

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.