# trade-hypothesis-ideator

Turns trade logs, journal notes and market data into falsifiable hypotheses with experiment designs and kill criteria.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 3200 installs · ★ 3267
- Author: tradermonty
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/tradermonty/claude-trading-skills/tree/HEAD/skills/trade-hypothesis-ideator/SKILL.md
- Updated: 2026-10-24
- HTML: https://affpapa.org/en/nevibecode/skills/trade-hypothesis-ideator

## What it does

The skill takes a normalized JSON bundle containing one or more of `trade_log`, `journal_snippets`, `market_data` or `observations`, and returns 1 to 5 hypothesis cards. Each card gets a verdict: `pursue`, `revise` or `discard`. Ranking happens in a second pass, after a critique step.

Work runs through `scripts/run_hypothesis_ideator.py` twice. Pass one normalizes the bundle and extracts an evidence summary. Pass two ranks the hypotheses and formats the output. Add `--export-strategies` and every `pursue` card is also written out as `strategy_<hypothesis_id>.yaml` plus `metadata_<hypothesis_id>.json`, in a format compatible with edge-finder-candidate/v1. The generation and critique prompts live in `prompts/`.

You need Python 3.9+ with `pyyaml` installed. No external API keys, since the calculation stays local. If all you have is scattered notes rather than a structured bundle, convert them to JSON first — pass one has nothing to normalize otherwise.

Output lands in `hypothesis_cards_<date>.json` and a readable `hypothesis_cards_<date>.md` with experiment designs and kill criteria. That pair is what you take to review before committing money to a test.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill trade-hypothesis-ideator -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/trade-hypothesis-ideator/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/trade-hypothesis-ideator/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill trade-hypothesis-ideator -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/trade-hypothesis-ideator/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill trade-hypothesis-ideator -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/trade-hypothesis-ideator/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install tradermonty/claude-trading-skills trade-hypothesis-ideator
```

2. **Manually: put the files in place**
- File: `.github/skills/trade-hypothesis-ideator/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill trade-hypothesis-ideator -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/tradermonty/claude-trading-skills --path skills/trade-hypothesis-ideator
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/trade-hypothesis-ideator/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add tradermonty/claude-trading-skills --skill trade-hypothesis-ideator -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/tradermonty/claude-trading-skills/tree/HEAD/skills/trade-hypothesis-ideator/SKILL.md

## When to use it
- turn scattered trade logs into falsifiable hypotheses
- rate evidence strength and drop weak ideas
- write experiment designs and exit conditions up front
- export a selected strategy to YAML for edge-finder
- compare several ideas against one ranking

## Example prompts
- here is a JSON bundle with my trade log and notes, generate and rank hypotheses
- run pass two and export the pursue cards to strategy.yaml
- tell me which hypotheses in this bundle are worth testing and which to drop

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 4b0ecffe175b075c.

BEGIN THIRD-PARTY FILE 4b0ecffe175b075c
````text
---
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`)
````
END THIRD-PARTY FILE 4b0ecffe175b075c

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