hypothesis-observation-review

hypothesis-observation-review is a skill for Claude Code, Codex from panjose/Co-Scientist. It costs 13 tokens per session (592 once invoked), scanned A, original, Apache-2.0.

A review step that tests a proposed explanation against observations collected during research. A hypothesis is a claim about what may explain something; observations are the recorded facts used to assess it.

In plain words
What is it for?
Use it to load a research plan and hypothesis, compare the hypothesis’s predictions with relevant observations, and record whether it explains them or is less plausible than alternatives.
Why use it?
It helps distinguish a genuinely explanatory hypothesis from one that merely shares a topic with the evidence or is contradicted by it.

Skill for Claude CodeCodex

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

Good fit Use it to load a research plan and hypothesis, compare the hypothesis’s predictions with relevant observations, and record whether it explains them or is less plausible than alternatives.

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

README.md
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Your own site
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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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Your own site · 80×15
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Per session 13 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 592 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 $0.00013 $0.00592
Opus 5 $0.00006 $0.00296
Sonnet 5 $0.00003 $0.00118
Haiku 4.5 $0.00001 $0.00059

Measured 11d ago against content hash c789e967881d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

hypothesis-observation-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 11d 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-observation-review/SKILL.md · 69 lines

What it actually says

hypothesis-observation-review

Goal:

  • Evaluate a hypothesis against prior observations.

Inputs:

  • research_plan/RESEARCH_PLAN.json
  • hypotheses/<id>/HYPOTHESIS.json
  • optional review guidance from prior review artifacts

Outputs:

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

Context Loading:

  • Read research_plan/RESEARCH_PLAN.json.
  • Read hypotheses/<id>/HYPOTHESIS.json.
  • Use the current hypothesis mechanism and predictions as the reference point for comparing against known observations.
  • If prior reviews exist, use them only to focus attention on disputed claims.

Execution Prompt Contract:

  • System Intent:
    • You are evaluating whether the hypothesis meaningfully explains relevant observations.
  • Required Reasoning Focus:
    • Look for observations that are causally relevant to the hypothesis domain.
    • Judge whether the hypothesis explains them, adds nothing, is contradicted by them, or is less plausible than existing explanations.
    • Prefer causal explanatory value over loose topical overlap.
  • Do Not Do:
    • Do not list observations that have no material connection to the hypothesis.
    • Do not treat generic correlation as causal support.
    • Do not emit free-form prose instead of structured observation entries.
  • Review Quality Floor:
    • A status = completed observation review must include concrete observations or retrieval results that are materially connected to the hypothesis mechanism or predicted behavior.
    • Each observation must explain why it supports, weakens, or remains neutral for the hypothesis rather than only naming a topic.
    • Do not use placeholder observation phrases such as consistent with prior observations, needs validation, or benchmark against parent as substantive review content.
  • Output Shape:
    • Produce the exact ObservationReviewContract from packages/agent_contracts/review.py.
    • Each observation entry must contain:
      • reasoning
      • conclusion
    • Use the allowed conclusion categories only.

Execution Steps:

  1. Open skills/shared-references/schema-index.md, then read packages/agent_contracts/review.py and confirm the exact ObservationReviewContract shape before writing OBSERVATION_REVIEW.json.
  2. Read the research plan and hypothesis.
  3. Identify the most relevant observations for the hypothesis domain.
  4. Evaluate whether the hypothesis explains, conflicts with, or adds little to each observation.
  5. Write hypotheses/<id>/REVIEW/OBSERVATION_REVIEW.json.
  6. Validate before declaring completion.

Artifact Rules:

  • Limit the review to the strongest and most relevant observations rather than padding the artifact.
  • Each observation entry must remain decision-oriented and concise.

Completion Rule:

  • This skill is complete only when OBSERVATION_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. 11d ago First seen · 69 lines · 13 tokens per session scan A c789e967881d

Subscribe to this mod's changes

hypothesis-observation-review is a skill published in the GitHub repository panjose/Co-Scientist (5 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 13 tokens to every session and 592 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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