hypothesis-generate-literature

hypothesis-generate-literature is a skill for Claude Code, Codex from panjose/Co-Scientist. It costs 20 tokens per session (1,226 once invoked), scanned A, original, Apache-2.0.

A research workflow that creates exactly one hypothesis candidate grounded in published literature. A hypothesis is a testable proposed explanation or prediction.

In plain words
What is it for?
Use it with a research plan, strategy, constraints, and literature evidence bundles to create hypothesis files and record their origin.
Why use it?
It gives a research process a traceable candidate based on collected evidence instead of an unsupported idea.

Skill for Claude CodeCodex

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

Good fit Use it with a research plan, strategy, constraints, and literature evidence bundles to create hypothesis files and record their origin.

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Install with agentmods
npx agentmods add skills/panjose/co-scientist/hypothesis-generate-literature
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-generate-literature
Clone the repo
git clone --depth 1 https://github.com/panjose/Co-Scientist

Made for: Claude Code, Codex.

Wrote this? Show the measurements

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README.md
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Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,226 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 $0.00020 $0.01226
Opus 5 $0.00010 $0.00613
Sonnet 5 $0.00004 $0.00245
Haiku 4.5 $0.00002 $0.00123

Measured 11d ago against content hash 2921b92ce267, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

hypothesis-generate-literature 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-generate-literature/SKILL.md · 88 lines

How it starts

The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.

hypothesis-generate-literature

Goal:

  • Generate exactly one literature-grounded hypothesis candidate for the active round.

Inputs:

  • research_plan/RESEARCH_PLAN.json
  • state/STRATEGY_PLAN.json
  • literature/queries/<query_id>/EVIDENCE_BUNDLE.json produced by tools.search_literature(...)
  • optional parent hypothesis and review artifacts when the round is part of an evolution continuation

Outputs:

  • hypotheses/<id>/HYPOTHESIS.json
  • hypotheses/<id>/HYPOTHESIS.md
  • hypotheses/<id>/ORIGIN.json
  • literature/queries/<query_id>/* search bridge artifacts for the evidence query used by this generation

Context Loading:

  • Open skills/shared-references/schema-index.md.
  • Open skills/shared-references/literature-search-contract.md.
  • Read packages/agent_contracts/literature.py before building or consuming any search bridge request or evidence bundle.
  • Read research_plan/RESEARCH_PLAN.json.
  • Treat research_goal as the task anchor.
  • Treat preferences as the quality axes that the hypothesis should optimize for.
  • Treat constraints as hard boundaries that the hypothesis and experiment design must satisfy.
  • Read state/STRATEGY_PLAN.json and confirm that the current round allows literature_exploration_generation.
  • If the round is parented, read the selected parent hypothesis and its latest review summary before generating a child. Improve the known weaknesses instead of paraphrasing the parent.

Execution Prompt Contract:

  • System Intent:
    • You are generating one scientifically grounded candidate hypothesis from literature exploration.
  • Required Reasoning Focus:
    • Before generating the candidate, call tools.search_literature(run_dir, request) with consumer="hypothesis-generate-literature" and use the returned EvidenceBundleContract as the formal external evidence input.
    • Use relevant prior work, gaps, contradictions, or unexplored connections from the evidence bundle to motivate the candidate.
    • Produce a specific falsifiable claim with a mechanism and a concrete experiment path.
    • Make the mechanism explicit enough that another reviewer can critique it step by step.
    • When novelty depends on a conjectural link, keep that link explicit rather than hiding it in vague wording.
  • Do Not Do:
    • Do not merely restate established literature.
    • Do not emit multiple final candidates in one round.
    • Do not ignore explicit constraints from the research plan.
    • Do not write an informal summary in place of the canonical hypothesis artifact.
    • Do not invent papers, DOIs, arXiv IDs, venues, citation counts, abstracts, or literature claims not present in the evidence bundle.
    • Do not treat model memory as a substitute for tools.search_literature(...).
  • Output Shape:
    • Wrap the final result into the canonical shared HypothesisContract.
    • origin.content.statement: 2-3 sentences maximum.
    • origin.content.mechanism: 2-3 sentences maximum.
    • origin.content.experimental_design: one concise multiline string with 3-6 numbered steps.
    • origin.content.experimental_design must remain one string field containing embedded line breaks; do not emit it as a list, array, or nested object.
    • origin.content.summary: one concise sentence.
    • origin.content.category: 1-5 words.

Execution Steps:

  1. Open skills/shared-references/schema-index.md, skills/shared-references/literature-search-contract.md, then read packages/agent_contracts/hypothesis.py and packages/agent_contracts/literature.py before writing hypotheses/<id>/HYPOTHESIS.json or consuming search bridge artifacts.
  2. Read the required artifacts.
  3. Confirm that this round is allowed to use literature exploration.
  4. Build a focused SearchRequestContract for the active research goal and call tools.search_literature(run_dir, request).
  5. Read the returned EvidenceBundleContract. If retrieval_metadata.status is blocked, stop or return a degraded state; do not write a literature-grounded hypothesis.
  6. Identify one literature-grounded gap or underexplored mechanism from the evidence bundle that can answer the active research goal.
  7. Generate exactly one candidate hypothesis for this round.
  8. Wrap the result into the canonical HypothesisContract. Any origin.retrieval_results entries must be derived from the evidence bundle rather than invented in prompt text.
  9. Write hypotheses/<id>/HYPOTHESIS.json, hypotheses/<id>/HYPOTHESIS.md, and hypotheses/<id>/ORIGIN.json.
  10. Validate the emitted artifacts before declaring success.

Read the full file on GitHub · 88 lines

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 · 88 lines · 20 tokens per session scan A 2921b92ce267

Subscribe to this mod's changes

hypothesis-generate-literature is a skill published in the GitHub repository panjose/Co-Scientist (5 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 20 tokens to every session and 1,226 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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