hypothesis-review-summary

hypothesis-review-summary is a skill for Claude Code, Codex from panjose/Co-Scientist. It costs 15 tokens per session (581 once invoked), scanned A, original, Apache-2.0.

A file-based aid for producing a compact summary of completed reviews of a hypothesis. A hypothesis is a proposed explanation or claim that is being evaluated.

In plain words
What is it for?
Use it to read a hypothesis and its completed review artifacts, then create a summary of the main strengths, weaknesses, and recommended next actions.
Why use it?
It combines the strongest findings across review stages while removing repetition, so the next decision is based on the existing evidence.

Skill for Claude CodeCodex

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

Good fit Use it to read a hypothesis and its completed review artifacts, then create a summary of the main strengths, weaknesses, and recommended next actions.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/panjose/co-scientist/hypothesis-review-summary/github.svg)](https://agentmods.dev/skills/panjose/co-scientist/hypothesis-review-summary)
Your own site
<a href="https://agentmods.dev/skills/panjose/co-scientist/hypothesis-review-summary"><img src="https://agentmods.dev/badge/skills/panjose/co-scientist/hypothesis-review-summary/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.

agentmods 80×15 button for hypothesis-review-summary

Your own site · 80×15
<a href="https://agentmods.dev/skills/panjose/co-scientist/hypothesis-review-summary"><img src="https://agentmods.dev/badge/skills/panjose/co-scientist/hypothesis-review-summary.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 15 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 581 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 $0.00581
Opus 5 $0.00008 $0.00291
Sonnet 5 $0.00003 $0.00116
Haiku 4.5 $0.00002 $0.00058

Measured 12d ago against content hash f49e77bc5c6e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

hypothesis-review-summary 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 12d 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-review-summary/SKILL.md · 65 lines

What it actually says

hypothesis-review-summary

Goal:

  • Summarize the completed reviews for a hypothesis.

Inputs:

  • hypotheses/<id>/HYPOTHESIS.json
  • completed review artifacts under hypotheses/<id>/REVIEW/

Outputs:

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

Context Loading:

  • Read hypotheses/<id>/HYPOTHESIS.json.
  • Read all completed review artifacts under hypotheses/<id>/REVIEW/.
  • Focus on synthesizing the strongest strengths, weaknesses, and recommended next actions across those reviews.

Execution Prompt Contract:

  • System Intent:
    • You are synthesizing the completed review stack into a compact downstream summary.
  • Required Reasoning Focus:
    • Deduplicate repeated points across review stages.
    • Preserve the most important strengths, weaknesses, and action items.
    • Prefer high-signal synthesis over exhaustive restatement.
  • Do Not Do:
    • Do not summarize reviews that do not exist.
    • Do not copy every review point verbatim.
    • Do not invent a new evaluation framework at summary time.
  • Review Quality Floor:
    • A status = completed review summary must synthesize concrete findings from completed review stages.
    • Include the strongest actionable strength, weakness, or next-step implication when those appear in prior reviews.
    • Do not use placeholder summary phrases such as Viable evolved hypothesis, Refined from parent, strong candidate, or needs validation as substantive summary content.
  • Output Shape:
    • Produce the exact ReviewSummaryContract from packages/agent_contracts/review.py.
    • Keep the summary as a compact list of downstream-usable points.
    • Each item in summaries must be a plain string, not an object with nested keys such as review_stage, outcome, or summary.

Execution Steps:

  1. Open skills/shared-references/schema-index.md, then read packages/agent_contracts/review.py and confirm the exact ReviewSummaryContract shape before writing REVIEW_SUMMARY.json.
  2. Read the current hypothesis and all completed review artifacts.
  3. Identify repeated themes and high-signal findings.
  4. Synthesize them into a compact summary list.
  5. Write hypotheses/<id>/REVIEW/REVIEW_SUMMARY.json.
  6. Validate before declaring completion.

Artifact Rules:

  • REVIEW_SUMMARY.json is a synthesis artifact, not a copy of all prior review text.
  • The summary must remain self-contained enough for downstream generation or ranking stages to consume quickly.

Completion Rule:

  • This skill is complete only when REVIEW_SUMMARY.json exists and is valid for downstream consumption.
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. 12d ago First seen · 65 lines · 15 tokens per session scan A f49e77bc5c6e

Subscribe to this mod's changes

hypothesis-review-summary 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 581 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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