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 Zaoqu-Liu/ScienceClaw --skill fair-datagit clone --depth 1 https://github.com/Zaoqu-Liu/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/zaoqu-liu/scienceclaw/fair-data)<a href="https://agentmods.dev/skills/zaoqu-liu/scienceclaw/fair-data"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/fair-data/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/zaoqu-liu/scienceclaw/fair-data"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/fair-data.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 | $0.00000 | $0.00370 |
| Opus 5 | $0.00000 | $0.00185 |
| Sonnet 5 | $0.00000 | $0.00074 |
| Haiku 4.5 | $0.00000 | $0.00037 |
Grade A, and why
fair-data 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 7d 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:
- fair-data — 100% identical, 0 lines differ
What it actually says
FAIR Data Principles — Findable, Accessible, Interoperable, Reusable
Overview
Guidelines for making scientific data FAIR: Findable, Accessible, Interoperable, and Reusable.
Findable
- Assign globally unique persistent identifiers (DOIs) to datasets
- Rich metadata describing the dataset (title, authors, description, keywords, dates)
- Metadata registered in searchable resources (DataCite, re3data, FAIRsharing)
- Data indexed in domain-specific repositories
Accessible
- Data retrievable by identifier using standardized protocol (HTTP, FTP)
- Metadata accessible even if data is restricted
- Authentication/authorization where necessary, clearly documented
- Long-term preservation plan (minimum 10 years for funded research)
Interoperable
- Use formal, shared vocabularies (ontologies: GO, ChEBI, EFO, MeSH)
- Standard file formats (CSV, JSON, HDF5, NetCDF — not proprietary)
- Include references to related datasets and publications
- Machine-readable metadata (JSON-LD, Dublin Core, schema.org)
Reusable
- Clear data usage license (CC-BY, CC0 recommended for scientific data)
- Detailed provenance (how data was collected, processed, quality controlled)
- Meet community standards (MIAME for microarrays, MINSEQE for sequencing)
- Version control for datasets that evolve
Recommended Repositories
| Domain | Repository |
|---|---|
| General | Zenodo, Figshare, Dryad |
| Genomics | GEO, SRA, ENA |
| Proteomics | PRIDE, MassIVE |
| Structures | PDB, EMDB |
| Clinical | ClinicalTrials.gov, YODA |
| Chemistry | ChEMBL, PubChem |
| Materials | NOMAD, Materials Cloud |
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.
- 7d ago First seen · 40 lines · 0 tokens per session scan A a8c702e31f66
fair-data is a skill published in the GitHub repository Zaoqu-Liu/ScienceClaw (60 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 370 tokens. 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 2026-09-03.
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