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.
npx skills add panjose/Co-Scientist --skill hypothesis-generate-literaturegit clone --depth 1 https://github.com/panjose/Co-ScientistWrote 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.
[](https://agentmods.dev/skills/panjose/co-scientist/hypothesis-generate-literature)<a href="https://agentmods.dev/skills/panjose/co-scientist/hypothesis-generate-literature"><img src="https://agentmods.dev/badge/skills/panjose/co-scientist/hypothesis-generate-literature/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.
<a href="https://agentmods.dev/skills/panjose/co-scientist/hypothesis-generate-literature"><img src="https://agentmods.dev/badge/skills/panjose/co-scientist/hypothesis-generate-literature.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once 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 |
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.
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.jsonstate/STRATEGY_PLAN.jsonliterature/queries/<query_id>/EVIDENCE_BUNDLE.jsonproduced bytools.search_literature(...)- optional parent hypothesis and review artifacts when the round is part of an evolution continuation
Outputs:
hypotheses/<id>/HYPOTHESIS.jsonhypotheses/<id>/HYPOTHESIS.mdhypotheses/<id>/ORIGIN.jsonliterature/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.pybefore building or consuming any search bridge request or evidence bundle. - Read
research_plan/RESEARCH_PLAN.json. - Treat
research_goalas the task anchor. - Treat
preferencesas the quality axes that the hypothesis should optimize for. - Treat
constraintsas hard boundaries that the hypothesis and experiment design must satisfy. - Read
state/STRATEGY_PLAN.jsonand confirm that the current round allowsliterature_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)withconsumer="hypothesis-generate-literature"and use the returnedEvidenceBundleContractas 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.
- Before generating the candidate, call
- 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_designmust 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.
- Wrap the final result into the canonical shared
Execution Steps:
- Open
skills/shared-references/schema-index.md,skills/shared-references/literature-search-contract.md, then readpackages/agent_contracts/hypothesis.pyandpackages/agent_contracts/literature.pybefore writinghypotheses/<id>/HYPOTHESIS.jsonor consuming search bridge artifacts. - Read the required artifacts.
- Confirm that this round is allowed to use literature exploration.
- Build a focused
SearchRequestContractfor the active research goal and calltools.search_literature(run_dir, request). - Read the returned
EvidenceBundleContract. Ifretrieval_metadata.statusisblocked, stop or return a degraded state; do not write a literature-grounded hypothesis. - Identify one literature-grounded gap or underexplored mechanism from the evidence bundle that can answer the active research goal.
- Generate exactly one candidate hypothesis for this round.
- Wrap the result into the canonical
HypothesisContract. Anyorigin.retrieval_resultsentries must be derived from the evidence bundle rather than invented in prompt text. - Write
hypotheses/<id>/HYPOTHESIS.json,hypotheses/<id>/HYPOTHESIS.md, andhypotheses/<id>/ORIGIN.json. - Validate the emitted artifacts before declaring success.
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.
- 11d ago First seen · 88 lines · 20 tokens per session scan A 2921b92ce267
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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