Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/fmschulz/omics-skillsnpx agentmods add skills/fmschulz/omics-skills/bio-foundation-housekeepingWrote 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/fmschulz/omics-skills/bio-foundation-housekeeping)<a href="https://agentmods.dev/skills/fmschulz/omics-skills/bio-foundation-housekeeping"><img src="https://agentmods.dev/badge/skills/fmschulz/omics-skills/bio-foundation-housekeeping/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/fmschulz/omics-skills/bio-foundation-housekeeping"><img src="https://agentmods.dev/badge/skills/fmschulz/omics-skills/bio-foundation-housekeeping.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 | $0.00046 | $0.01629 |
| Opus 5 | $0.00023 | $0.00814 |
| Sonnet 5 | $0.00009 | $0.00326 |
| Haiku 4.5 | $0.00005 | $0.00163 |
Grade A, and why
bio-foundation-housekeeping 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 10d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bio Foundation Housekeeping
Add validated metadata models and a queryable catalog to an existing bioinformatics project. This is an independent entry point when the layout already exists; if it does not, complete bioinformatics-project as a separate setup task.
Instructions
- Confirm
bioinformatics-projecthas established input/output boundaries, project records, and a pinned environment. Do not create a competing project layout. - Adapt
schemas/project-metadata.yamlfor the sample, run, file, result, and provenance records the project needs. Keep identifiers stable and declare types, required fields, enumerations, and patterns in the schema. - Generate Pydantic models with
scripts/generate_models.py. The command pins LinkML and Pydantic, rejects changed outputs, imports the generated module, and can assert that expected classes exist. - Validate the complete metadata bundle with the generated
MetadataBundlemodel. Reject unexpected fields and malformed types before checking relationships. - Check unique identifiers and foreign keys across record collections before writing outputs. At minimum, verify run-to-sample, file-to-run, result-to-input/output-file, and provenance-to-result links.
- Normalize validated records into one Parquet table per record class plus bridge tables for multivalued relationships. Register the tables and their relative paths, row counts, and SHA-256 values in DuckDB.
- Exercise the full boundary with
scripts/build_metadata_catalog.pyand the bundled valid, model-invalid, and foreign-key-invalid fixtures. Usescripts/build_sample_catalog.pyonly for the smaller sample-only smoke path. - Before adopting a project-specific extension or migrating stored records, run
scripts/check_schema_compatibility.py. Optional slots and new classes are compatible; required additions and constraint changes are reported as breaking. Keep a versioned input/expected migration fixture likefixtures/schema-migration-v1-to-v1.1.jsonfor every supported transition.
What ships with it
20 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.
- docs/duckdb.md 11 KB
- docs/linkml.md 7.7 KB
- docs/pixi.md 5.5 KB
- docs/pydantic.md 9.2 KB
- docs/README.md 3.7 KB
- fixtures/invalid-foreign-keys.json 971 B
- fixtures/invalid-project-metadata.json 278 B
- fixtures/invalid-provenance-cardinality.json 1.8 KB
- fixtures/invalid-result-relations.json 3.1 KB
- fixtures/invalid-samples.jsonl 147 B
- fixtures/schema-extension-breaking.yaml 226 B
- fixtures/schema-extension-compatible.yaml 170 B
- fixtures/schema-migration-v1-to-v1.1.json 316 B
- fixtures/valid-project-metadata.json 1.9 KB
- fixtures/valid-samples.jsonl 298 B
- schemas/project-metadata.yaml 5.0 KB
- scripts/build_metadata_catalog.py 19 KB runs code
- scripts/build_sample_catalog.py 8.3 KB runs code
- scripts/check_schema_compatibility.py 3.0 KB runs code
- scripts/generate_models.py 3.5 KB runs code
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.
- 10d ago First seen · 125 lines · 46 tokens per session scan A 15fb1ad0b637
bio-foundation-housekeeping is a skill published in the GitHub repository fmschulz/omics-skills (7 stars, last pushed 5d ago), licensed MIT. It adds 46 tokens to every session and 1,629 once invoked, about $0.0002 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.
Other skills, from other repositories
lamindb
Use when working with LaminDB, the open-source lineage-native lakehouse for biological datasets and models. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation with Bionty, collections, branches, storage, and workflow integrations.
tiledbvcf
Efficient storage and retrieval of genomic variant data using TileDB. Scalable VCF/BCF ingestion, incremental sample addition, compressed storage, parallel queries, and export capabilities for population genomics.
imaging-data-commons
Query and download public cancer imaging data from NCI Imaging Data Commons. Invoke for any question about IDC collections, cancer imaging datasets, DICOM data access, radiology (CT, MR, PET) or pathology AI training sets, metadata queries, visualization, or license checks — even when the user doesn't explicitly…
tamarind
Access a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design…
lab-hardware-cad
Design custom laboratory hardware as parametric build123d models and export fabrication-ready STEP, STL, and DXF files - microfluidic chips and molds, optomechanical mounts and breadboard adapters, cuvette and microplate holders, tube racks, animal-behavior rigs, and 3D-printed instrument fixtures. Use when a research…
pkpd-modeling
Pharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when…