Specification
- Skill ID
- tradermonty/claude-trading-skills/trade-hypothesis-ideator
- Publisher
- tradermonty
- Repository
- claude-trading-skills
- Installs
- 0
- Files
- 28
- Synced
- Sep 23, 2026
How to use it
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
tradermonty/claude-trading-skills/trade-hypothesis-ideatorInstalls these files- SKILL.md
- examples/example_input.json
- examples/example_output.json
- examples/sample_input.json
- prompts/critique_prompt_template.md
- prompts/developer_prompt_template.md
- prompts/system_prompt.md
- references/evidence_quality_guide.md
- references/hypothesis_types.md
- requirements.txt
- schemas/hypothesis_card.schema.json
- schemas/input_bundle.schema.json
- schemas/output_bundle.schema.json
- schemas/raw_hypotheses.schema.json
- scripts/pipeline/__init__.py
- scripts/pipeline/evidence_extractor.py
- scripts/pipeline/format_output.py
- scripts/pipeline/normalize.py
- scripts/pipeline/ranking.py
- scripts/pipeline/strategy_exporter.py
- scripts/run_hypothesis_ideator.py
- scripts/tests/conftest.py
- scripts/tests/test_evidence_extractor.py
- scripts/tests/test_format_output.py
- scripts/tests/test_guardrails.py
- scripts/tests/test_normalize.py
- scripts/tests/test_ranking.py
- scripts/tests/test_strategy_exporter.py
What this skill tells the agent
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
pyyamlinstalled - 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.mdprompts/developer_prompt_template.md(inject{{evidence_summary}})
- Critique hypotheses with
prompts/critique_prompt_template.md. - Run pass 2 ranking + output formatting + guardrails.
- Optionally export
pursuehypotheses 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-strategiesOutput
hypothesis_cards_<date>.json— Ranked hypothesis cards with verdicts (pursue,revise,discard)hypothesis_cards_<date>.md— Human-readable summary with experiment designs and kill criteriastrategy_<hypothesis_id>.yaml— (Optional) Edge-finder-compatible strategy export forpursuecardsmetadata_<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
More from tradermonty
Use this skill in a project
Open any RiverX project, search the Skills panel for tradermonty/claude-trading-skills/trade-hypothesis-ideator, and install it in one click.
