Open Science is a local-first, model-agnostic workbench for reproducible scientific research. Scientists use its AI agents, Python and R execution, data connectors, and traceable outputs for tasks such as literature review, analysis, simulation, and visualization across macOS, Windows, and Linux.
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 aipoch/open-science --skill paper-narrativegit clone --depth 1 https://github.com/aipoch/open-scienceWrote 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/aipoch/open-science/paper-narrative)<a href="https://agentmods.dev/skills/aipoch/open-science/paper-narrative"><img src="https://agentmods.dev/badge/skills/aipoch/open-science/paper-narrative.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00058 | $0.03460 |
| Opus 5 | $0.00029 | $0.01730 |
| Sonnet 5 | $0.00012 | $0.00692 |
| Haiku 4.5 | $0.00006 | $0.00346 |
Grade A, and why
paper-narrative 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 8d 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 — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Narrative — manuscript → brief → figure arc → editorial loop
paper-narrative is the outermost figure workflow. It judges the paper-level
story before figure-composer designs any one figure. The inputs are the work
itself: a manuscript (or abstract), figure captions, and the current full deck.
Open Science Notebook call
Every notebook_execute request whose code uses a function named in this skill
includes this skill ID:
{ "kernelSkillIds": ["paper-narrative"], "code": "print(paper_brief_schema())" }
kernelSkillIds contains the skill ID; function calls belong in code. This
request is complete as written: call the named functions directly and do not add
an import or discovery step.
Required inputs and trust labels
Keep these inputs distinct throughout the workflow:
manuscriptVersionId: immutable manuscript Artifact Version (an abstract-only manuscript is allowed) and the reviewed manuscript text read from it.abstractText: reviewed abstract text when available; use it for bounded brief reasoning while retaining the full manuscript Version as source provenance.captionsVersionId: immutable captions Artifact Version and the reviewed per-figure caption or claim text read from it.deckVersionId: immutable deck Artifact Version containing every current figure in review order.rulesVersionId: immutable design-rules Artifact Version, used only as a reference so the editor judges story rather than visual craft.figureDataVersionIds: immutable data Artifact Versions grouped by figure.figureWidthMmByFigure: reviewed positive venue width for each figure; the downstream composer must not invent this physical output constraint.
Manuscript, captions, deck, and data are source inputs. Every brief, review, arc, move, omission, and proposed analysis is model-generated and requires human review. Never describe generated text as manuscript evidence or source data. Preserve the input Version identities when publishing or delegating downstream work.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 323 lines · 58 tokens per session scan A d90ad4cd40a5
paper-narrative is a skill published in the GitHub repository aipoch/open-science (3,964 stars, last pushed today), licensed Apache-2.0. It adds 58 tokens to every session and 3,460 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
build-paper-pipeline
Build the pipeline stages a manuscript's TODO comments ask for.
check-questions
Review a Calkit project's questions and answers against their evidence. Use when the user invokes /calkit:check-questions, asks whether the project's answers are still true, or after a pipeline run changes results that answers cite.
clinical-case-report
Structured medical case presentation for clinical rounds, conferences, and documentation. Generates SOAP-format or narrative case reports with physiologically accurate vitals, labs, and evidence-based plans. Use when the brief mentions "case report", "case presentation", "SOAP note", "clinical case", "ward rounds"…
proof-checker
A mathematical proof review and repair workflow for LaTeX documents. It checks whether a proof has valid reasoning, addresses identified gaps, reviews the fixes, and produces an audit report.
paper-illustration
A workflow for generating academic illustrations, such as architecture diagrams and method visuals, with image generation and repeated review. Claude plans and checks the figure during the process.
paper-illustration-image2
Generate publication-quality academic illustrations through a local Codex app-server bridge that uses Codex native image generation. This is a separate experimental alternative to paper-illustration, intended for Claude Code users who want a GPT-image-style renderer without modifying the original skill.