Trade Hypothesis Ideator

CommunityPopular

tradermonty

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.

Overview

Publisher	tradermonty
Repository	`claude-trading-skills`
Skill name	`trade-hypothesis-ideator`
Stars	2.9K
Forks	663
Bundled files	27
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
27 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by tradermonty on GitHub. Read the source before you install it.

Installation

Install the Trade Hypothesis Ideator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/tradermonty/claude-trading-skills/tree/main/skills/trade-hypothesis-ideator
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/tradermonty/claude-trading-skills/tree/main/skills/trade-hypothesis-ideator

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/tradermonty/claude-trading-skills.git /tmp/claude-trading-skills
mkdir -p .claude/skills
cp -r /tmp/claude-trading-skills/skills/trade-hypothesis-ideator .claude/skills/trade-hypothesis-ideator

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Trade Hypothesis Ideator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Trade Hypothesis Ideator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Trade Hypothesis Ideator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

Receive input JSON bundle.
Run pass 1 normalization + evidence extraction.
Generate hypotheses with prompts:
- prompts/system_prompt.md
- prompts/developer_prompt_template.md (inject {{evidence_summary}})
Critique hypotheses with prompts/critique_prompt_template.md.
Run pass 2 ranking + output formatting + guardrails.
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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Trade Hypothesis Ideator AI skill do?

Why use Trade Hypothesis Ideator on TypingMind?

Because you install it once and use it with any model. Trade Hypothesis Ideator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Trade Hypothesis Ideator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tradermonty/claude-trading-skills/tree/main/skills/trade-hypothesis-ideator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Trade Hypothesis Ideator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Trade Hypothesis Ideator?

As many as you like. As long as a model supports skills, you can use Trade Hypothesis Ideator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Trade Hypothesis Ideator AI skill free?

Yes. It is published on GitHub by tradermonty under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Gitcrawl

openclaw

OrganizationPopular

GitHub archive: issue/PR search, sync freshness, duplicate clusters, current GitHub handoff, and Gitcrawl repo work.

Graincrawl

Granola archive: search, sync freshness, notes, transcripts, panels, SQL counts, and Graincrawl repo work.

Openclaw Changelog Update

openclaw

OrganizationPopular

Regenerate OpenClaw release changelog sections from git history before beta, stable, or extended-stable releases.

Openclaw Ci Limits

Manage OpenClaw GitHub Actions and Blacksmith CI capacity, runner-registration budgets, fanout caps, main-push single-flight, shard sizing, hosted-runner offload, queue health, and safe…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Trade Hypothesis Ideator

When to Use

Prerequisites

Workflow

Scripts

Output

Resources

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now