ScienceClaw is an agent system for scientific work that completes tasks as typed, executable workflows and turns replay-verified improvements into reusable skills and operators. It is intended for AI-assisted research across natural and social science disciplines. The catalogue entries are its skills and instruction for use with the system.
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 beita6969/ScienceClaw --skill diffsgit clone --depth 1 https://github.com/beita6969/ScienceClawWrote 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/beita6969/scienceclaw/diffs)<a href="https://agentmods.dev/skills/beita6969/scienceclaw/diffs"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/diffs/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/beita6969/scienceclaw/diffs"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/diffs.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00032 | $0.00324 |
| Opus 5.5 | $0.00013 | $0.00130 |
| Sonnet 5.5 | $0.00006 | $0.00065 |
| Haiku 4.5 | $0.00003 | $0.00032 |
Grade A, and why
diffs 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- diffs — 100% identical, 0 lines differ
What it actually says
When you need to show edits as a real diff, prefer the diffs tool instead of writing a manual summary.
The diffs tool accepts either before + after text, or a unified patch string.
Use mode=view when you want an interactive gateway-hosted viewer. After the tool returns, use details.viewerUrl with the canvas tool via canvas present or canvas navigate.
Use mode=file when you need a rendered file artifact. Set fileFormat=png (default) or fileFormat=pdf. The tool result includes details.filePath.
For large or high-fidelity files, use fileQuality (standard|hq|print) and optionally override fileScale/fileMaxWidth.
When you need to deliver the rendered file to a user or channel, do not rely on the raw tool-result renderer. Instead, call the message tool and pass details.filePath through path or filePath.
Use mode=both when you want both the gateway viewer URL and the rendered artifact.
If the user has configured diffs plugin defaults, prefer omitting mode, theme, layout, and related presentation options unless you need to override them for this specific diff.
Include path for before/after text when you know the file name.
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.
- 1mo ago First seen · 23 lines · 32 tokens per session scan A 6fe3e6d74fad
diffs is a skill published in the GitHub repository beita6969/ScienceClaw (1,019 stars, last pushed 9d ago), licensed MIT. It adds 32 tokens to every session and 324 once invoked, about $0.0001 per session on Opus 5.5. 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
deployment-patterns
Deployment workflows, CI/CD pipeline patterns, Docker containerization, health checks, rollback strategies, and production readiness checklists for web applications. Use when setting up deployment infrastructure or planning releases.
datalad
Retrieves, versions, and publishes scientific datasets with DataLad and git-annex, and captures computational provenance with datalad run, rerun, and containers-run. Use when cloning or fetching data from OpenNeuro, DANDI, datasets.datalad.org, or any DataLad dataset; when a file in a dataset reads as a broken symlink…
resolve-handoff
Emit the complete Resolve handoff with exact modes, outcomes, test evidence, and publication state.
baby-sit
Monitor a GitHub pull request until CI is green, diagnose failures, and rerun only evidence-backed flaky GitHub Actions jobs.
merge-drive
Carry a long-running conflicted merge of origin/main into a branch that restructured the tree: read the merge state from the index, resolve by class, and hand it to the next session without losing work. Covers the classes git reports as already-resolved (silent resurrections, directory-rename ports, half-landed…
git-checkpoint
Use git as a safety net - create a checkpoint commit before risky or large changes and roll back cleanly if a change makes things worse. Use before multi-file refactors.