hypothesis-initial-review

hypothesis-initial-review is a skill for Claude Code, Codex from panjose/Co-Scientist. It costs 15 tokens per session (649 once invoked), scanned A, original, Apache-2.0.

An early review step for deciding whether a research hypothesis should move on to deeper evaluation.

In plain words
What is it for?
Use it to compare one hypothesis with the research goal, preferences, and constraints, then write an initial review result.
Why use it?
It catches major problems early without rejecting ideas that only need small improvements.

Skill for Claude CodeCodex

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

Good fit Use it to compare one hypothesis with the research goal, preferences, and constraints, then write an initial review result.

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

agentmods badge for hypothesis-initial-review

README.md
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Your own site
<a href="https://agentmods.dev/skills/panjose/co-scientist/hypothesis-initial-review"><img src="https://agentmods.dev/badge/skills/panjose/co-scientist/hypothesis-initial-review/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 649 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 $0.00015 $0.00649
Opus 5 $0.00008 $0.00324
Sonnet 5 $0.00003 $0.00130
Haiku 4.5 $0.00002 $0.00065

Measured 10d ago against content hash 39586151ece8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

hypothesis-initial-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 10d 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-initial-review/SKILL.md · 73 lines

What it actually says

hypothesis-initial-review

Goal:

  • Run the initial review gate for a hypothesis.

Inputs:

  • research_plan/RESEARCH_PLAN.json
  • hypotheses/<id>/HYPOTHESIS.json
  • optional meta/INSIGHTS_FROM_REVIEWS.json or other run-level review guidance when available

Outputs:

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

Context Loading:

  • Read research_plan/RESEARCH_PLAN.json.
  • Treat research_goal as the target problem.
  • Treat preferences as the main evaluation axes.
  • Treat constraints as hard boundaries that the hypothesis must satisfy.
  • Read hypotheses/<id>/HYPOTHESIS.json.
  • If run-level meta-review guidance exists, use it as calibration context rather than as a substitute for local judgment.

Execution Prompt Contract:

  • System Intent:
    • You are the rapid initial review gate for one hypothesis.
  • Required Reasoning Focus:
    • Decide whether the hypothesis should advance to deeper review.
    • Judge it against the explicit preference axes and constraints.
    • Distinguish between fundamental flaws and refinable weaknesses.
    • Borderline but refinable hypotheses should usually pass.
  • Do Not Do:
    • Do not perform a full literature-grounded review here.
    • Do not fail a hypothesis for minor polish issues alone.
    • Do not emit unstructured commentary in place of the review artifact.
  • Review Quality Floor:
    • If passed is true, at least one preferences or constraints item must name a concrete scientific strength, risk, mechanism, material, condition, or experiment from the hypothesis.
    • Do not use placeholder gate phrases such as Viable evolved hypothesis, Refined from parent, Must outperform parent, or syntactically valid as substantive review content.
    • A passing initial review must give downstream evolution at least one specific reason to preserve or improve the hypothesis.
  • Output Shape:
    • Produce the exact InitialReviewContract from packages/agent_contracts/review.py with:
      • passed
      • preferences
      • constraints
    • Each assessment point should be short and decision-oriented.

Execution Steps:

  1. Open skills/shared-references/schema-index.md, then read packages/agent_contracts/review.py and confirm the exact InitialReviewContract shape before writing INITIAL_REVIEW.json.
  2. Read the research plan and current hypothesis.
  3. Review the hypothesis against each preference axis.
  4. Review the hypothesis against each constraint.
  5. Make a pass/fail decision.
  6. Write hypotheses/<id>/REVIEW/INITIAL_REVIEW.json.
  7. Validate before declaring completion.

Artifact Rules:

  • INITIAL_REVIEW.json must be a structured artifact, not a free-form memo.
  • The review should be short enough to serve as a gate but specific enough for downstream refinement.

Completion Rule:

  • This skill is complete only when INITIAL_REVIEW.json exists and is valid for downstream review routing.
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. 10d ago First seen · 73 lines · 15 tokens per session scan A 39586151ece8

Subscribe to this mod's changes

hypothesis-initial-review is a skill published in the GitHub repository panjose/Co-Scientist (5 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 15 tokens to every session and 649 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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