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.
npx skills add BaggaT236/AI-Trading-Skills --skill trade-hypothesis-ideator --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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
- When to Use
- Prerequisites
- Workflow
- Scripts
- Output
- Resources
python3 skills/trade-hypothesis-ideator/scripts/run_hypothesis_ideator.py \
What does the trade-hypothesis-ideator skill do?
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.
How do I install it?
Run `npx skills add BaggaT236/AI-Trading-Skills --skill trade-hypothesis-ideator --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BaggaT236/AI-Trading-Skills, a repository with 118 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.