hypothesis-simulation-review

hypothesis-simulation-review is a skill for Claude Code, Codex from panjose/Co-Scientist. It costs 16 tokens per session (655 once invoked), scanned A, original, Apache-2.0.

A review tool that walks through a research hypothesis step by step and looks for ways its proposed mechanism or testing process could fail.

In plain words
What is it for?
Use it to review a research plan and hypothesis, producing a simulation review artifact.
Why use it?
It turns a vague critique into concrete failure scenarios and separates fundamental problems from implementation issues.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to review a research plan and hypothesis, producing a simulation review artifact.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/panjose/co-scientist/hypothesis-simulation-review
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add panjose/Co-Scientist --skill hypothesis-simulation-review
Clone the repo
git clone --depth 1 https://github.com/panjose/Co-Scientist

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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Your own site
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Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 655 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00016 $0.00655
Opus 5 $0.00008 $0.00328
Sonnet 5 $0.00003 $0.00131
Haiku 4.5 $0.00002 $0.00065

Measured 9d ago against content hash 9aa337626696, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

hypothesis-simulation-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/hypothesis-simulation-review/SKILL.md · 71 lines

What it actually says

hypothesis-simulation-review

Goal:

  • Simulate the hypothesis mechanism and identify failure scenarios.

Inputs:

  • research_plan/RESEARCH_PLAN.json
  • hypotheses/<id>/HYPOTHESIS.json
  • optional prior review artifacts for calibration

Outputs:

  • hypotheses/<id>/REVIEW/SIMULATION_REVIEW.json

Context Loading:

  • Read research_plan/RESEARCH_PLAN.json.
  • Read hypotheses/<id>/HYPOTHESIS.json.
  • Use prior reviews only as hints for likely weak spots; the simulation should still be an independent walk-through of the mechanism and validation path.

Execution Prompt Contract:

  • System Intent:
    • You are mentally simulating the hypothesis mechanism and proposed validation path step by step.
  • Required Reasoning Focus:
    • Break the mechanism into an ordered process.
    • Identify where the process could fail and why.
    • Distinguish inherent failures from contingent implementation issues where possible.
    • Prioritize likely and fundamental failure scenarios over edge cases.
  • Do Not Do:
    • Do not generate abstract critique without a concrete simulated step.
    • Do not flood the artifact with low-value edge cases.
    • Do not replace the structured review with narrative prose.
  • Review Quality Floor:
    • A status = completed simulation review must include concrete mechanism or validation steps and concrete failure scenarios.
    • Steps must name hypothesis-specific materials, mechanisms, measurements, conditions, controls, or decision points.
    • Do not use placeholder simulation steps such as Synthesize evolved catalyst, Characterize structure, Test activity, or Benchmark against parent as substantive review content.
  • Output Shape:
    • Produce the exact SimulationReviewContract from packages/agent_contracts/review.py with:
      • steps
      • failure_scenarios
    • Keep each step and failure scenario concise and concrete.
    • Each item in steps must be a plain string, not an object with nested keys such as step, description, or expected_outcome.
    • Each item in failure_scenarios must be a plain string, not an object with nested keys such as scenario, likelihood, or mitigation.

Execution Steps:

  1. Open skills/shared-references/schema-index.md, then read packages/agent_contracts/review.py and confirm the exact SimulationReviewContract shape before writing SIMULATION_REVIEW.json.
  2. Read the research plan and hypothesis.
  3. Simulate the key mechanism or validation path step by step.
  4. Record the major steps.
  5. Identify likely and fundamental failure scenarios.
  6. Write hypotheses/<id>/REVIEW/SIMULATION_REVIEW.json.
  7. Validate before declaring completion.

Artifact Rules:

  • SIMULATION_REVIEW.json should focus on the highest-signal failure modes.
  • The artifact should remain short enough for downstream summarization but concrete enough to guide revision.

Completion Rule:

  • This skill is complete only when SIMULATION_REVIEW.json exists and is valid for downstream synthesis.
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 71 lines · 16 tokens per session scan A 9aa337626696

Subscribe to this mod's changes

hypothesis-simulation-review is a skill published in the GitHub repository panjose/Co-Scientist (5 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 16 tokens to every session and 655 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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