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.
Scanned 9/2/2026
Install to Claude Code
npx -y skills add Serennity007/awesome-stock-quant-skills --skill trade-hypothesis-ideator --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: trade-hypothesis-ideator
description: >
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.
---
# 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):
```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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