Vibe-Skills is a collection and routing system that helps AI agents discover, select, and coordinate specialized skills for completing tasks. It is intended for agents that need to organize workflows across many installed capabilities. The catalogue entries are skills and an agent belonging to this 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 foryourhealth111-pixel/Vibe-Skills --skill bio-database-evidencegit clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-SkillsWrote 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/foryourhealth111-pixel/vibe-skills/bio-database-evidence)<a href="https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/bio-database-evidence"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/bio-database-evidence/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/foryourhealth111-pixel/vibe-skills/bio-database-evidence"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/bio-database-evidence.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 | $0.00101 | $0.00640 |
| Opus 5 | $0.00051 | $0.00320 |
| Sonnet 5 | $0.00020 | $0.00128 |
| Haiku 4.5 | $0.00010 | $0.00064 |
Grade A, and why
bio-database-evidence 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 13d 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 — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bio Database Evidence
Use This Skill For
Use this skill when the main task is biological database lookup, annotation, or evidence gathering across one or more biological sources:
- Gene annotation, identifiers, RefSeq, Ensembl IDs, orthologs, VEP, GO, and genomic coordinates.
- Variant clinical significance, VUS interpretation support, ClinVar review status, cancer mutations, and COSMIC evidence.
- GWAS Catalog trait associations, rs IDs, p-values, summary statistics, and genetic epidemiology evidence.
- Pathway mapping, ID conversion, KEGG pathways, Reactome enrichment, disease pathways, and pathway evidence.
- Target-disease association evidence, tractability, safety, known drugs, and Open Targets evidence.
- Protein structure evidence from AlphaFold DB or RCSB PDB, including UniProt IDs, mmCIF/PDB downloads, pLDDT, PAE, and structure metadata.
- Protein-protein interaction evidence, STRING networks, hub proteins, and enrichment evidence.
- Reference single-cell data lookup from CELLxGENE Census when the user asks for census metadata or expression data, not full downstream analysis.
- Cross-database biological ID mapping and evidence tables across multiple resources.
Do Not Use This Skill For
- Single-cell RNA-seq analysis, clustering, UMAP, marker genes, cell annotation, AnnData/h5ad container editing, or scVI/scANVI batch-correction planning. Use
scanpy. - Bulk RNA-seq differential expression. Use
pydeseq2. - BAM, SAM, CRAM, VCF, pileup, coverage, or region extraction as a primary file-processing task.
- deepTools signal-track processing and heatmaps.
- Protein language models, embeddings, inverse folding, or protein-design workflows.
- Constraint-based metabolic modeling, FBA, or metabolic-engineering simulation.
- BED/genomic interval embeddings, genomic-region ML, or gene regulatory network inference.
- FCS or flow-cytometry file parsing.
Workflow
- Identify the biological entity type: gene, transcript, variant, pathway, target, protein structure, protein interaction, trait association, or reference cell population.
- Pick the narrowest source that answers the evidence question.
- Preserve source names, query terms, access dates, identifiers, and API caveats in the result.
- Return evidence in a table when comparing multiple sources.
- State when authentication, license, rate limits, or non-public access restricts a source.
What ships with it
1 file 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.
- 13d ago First seen · 44 lines · 101 tokens per session scan A b7651c5be518
bio-database-evidence is a skill published in the GitHub repository foryourhealth111-pixel/Vibe-Skills (3,262 stars, last pushed 12d ago), licensed Apache-2.0. It adds 101 tokens to every session and 640 once invoked, about $0.0005 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.
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