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 dralkh/seerai --skill database-lookupgit clone --depth 1 https://github.com/dralkh/seeraiWrote 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/dralkh/seerai/database-lookup)<a href="https://agentmods.dev/skills/dralkh/seerai/database-lookup"><img src="https://agentmods.dev/badge/skills/dralkh/seerai/database-lookup.svg" alt="Measured on agentmods" 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 | $0.00082 | $0.08227 |
| Opus 5 | $0.00041 | $0.04113 |
| Sonnet 5 | $0.00016 | $0.01645 |
| Haiku 4.5 | $0.00008 | $0.00823 |
Grade B, and why
database-lookup scanned grade B with 2 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
| Open Targets | GraphQL endpoint | `curl -X POST -H "Content-Type: application/json" -d '{"query":"..."}' https://api.platform.opentargets.org/api/v4/graphql` | Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
These databases require HTTP POST and **will not work with WebFetch** (GET-only). Use `curl` via your platform's shell tool instead: This is a copy
100% identical to database-lookup — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 522 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Lookup
You have access to 78 public databases through documented REST APIs. Your job is to turn the user's intent into a reproducible retrieval: select the authoritative database(s), make complete and rate-limited API calls, verify counts when completeness matters, and return results with enough provenance that another agent or human can repeat the lookup.
For complex biomedical retrievals, assume small filtering differences can change downstream conclusions. Prefer deterministic APIs, explicit identifiers, exhaustive pagination, and auditable logs over broad searching or plausible summaries.
Core Workflow
-
Define the retrieval contract — Identify the target entity, accepted identifiers, organism/taxon/build/date constraints, filters, expected output fields, and whether the user needs an exhaustive dataset or a targeted lookup. If a required scientific constraint is missing and affects correctness, ask a clarifying question rather than guessing.
-
Select authoritative database(s) — Use the database selection guide below. Prefer the primary database for the user's intent, then add cross-check databases only for identifier resolution, validation, or known coverage gaps. Do not fan out across many APIs just because they are available.
-
Read the reference file and retrieval contract — Each database has a reference file in
references/with endpoint details, query formats, and example calls. Read the relevant file(s) andreferences/retrieval-contract.mdbefore making API calls. -
Plan filter semantics before calling — Separate filters the API enforces server-side from filters that must be checked locally. Note identifier conversions, fields with ambiguous meanings, pagination strategy, rate limits, and any data-source conventions such as RefSeq vs GenBank or genome build.
-
Make complete API calls — See the Making API Calls section below. For exhaustive retrievals, count first when the API supports it, paginate or batch until retrieved counts reconcile, and fail visibly if the final dataset is incomplete.
What ships with it
60 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.
- references/addgene.md 960 B
- references/alphafold.md 1023 B
- references/alphavantage.md 7.5 KB
- references/bea.md 14 KB
- references/bindingdb.md 2.9 KB
- references/biogrid.md 3.6 KB
- references/bls.md 9.1 KB
- references/brenda.md 2.2 KB
- references/cbioportal.md 7.1 KB
- references/census.md 8.5 KB
- references/chebi.md 3.3 KB
- references/chembl.md 2.3 KB
- references/clinicaltrials.md 2.1 KB
- references/clinpgx.md 1.2 KB
- references/clinvar.md 3.1 KB
- references/cod.md 2.7 KB
- references/cosmic.md 1.4 KB
- references/dailymed.md 1.7 KB
- references/datacommons.md 6.9 KB
- references/dbsnp.md 3.2 KB
- references/disgenet.md 1.4 KB
- references/drugbank.md 1.6 KB
- references/ecb.md 6.2 KB
- references/emdb.md 895 B
- references/ena.md 9.5 KB
- references/encode.md 1.5 KB
- references/ensembl.md 13 KB
- references/epa.md 6.3 KB
- references/eurostat.md 7.4 KB
- references/fda.md 1.9 KB
- references/federal-reserve.md 6.7 KB
- references/fred.md 9.9 KB
- references/gene-ontology.md 4.2 KB
- references/geo.md 3.7 KB
- references/gnomad.md 2.9 KB
- references/gtex.md 3.6 KB
- references/gwas-catalog.md 1.4 KB
- references/hca.md 870 B
- references/hpo.md 1.4 KB
- references/human-protein-atlas.md 1.3 KB
- references/interpro.md 3.3 KB
- references/jaspar.md 1.4 KB
- references/kegg.md 2.3 KB
- references/lincs-l1000.md 1.9 KB
- references/materials-project.md 3.3 KB
- references/metabolomics-workbench.md 3.3 KB
- references/monarch.md 1.4 KB
- references/mousemine.md 1.2 KB
- references/nasa-exoplanet-archive.md 4.0 KB
- references/nasa.md 3.1 KB
- references/ncbi-gene.md 1.6 KB
- references/ncbi-protein.md 2.9 KB
- references/ncbi-taxonomy.md 3.4 KB
- references/nist.md 3.4 KB
- references/noaa.md 6.3 KB
- references/omim.md 3.2 KB
- references/opentargets.md 8.7 KB
- references/openweathermap.md 6.9 KB
- references/pdb.md 2.8 KB
- references/pride.md 2.2 KB
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 · 522 lines · 82 tokens per session scan B eec04f1c4c12
database-lookup is a skill published in the GitHub repository dralkh/seerai (76 stars, last pushed 1mo ago), licensed MIT. It adds 82 tokens to every session and 8,227 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). It is 100% identical to database-lookup, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
sn-search-academic
An academic research tool for finding papers and encyclopedia entries, reading papers in full or by section, and tracing references and citations. It supports structured literature research.
paper-revision-author
Revise independently drafted paper sections into one coherent LaTeX body before the abstract is written.
imaging-data-commons
Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.
clinical-decision-support
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading…
molecular-cloning
Molecular cloning simulation and design. PCR amplicon prediction, restriction enzyme digestion, Golden Gate and Gibson assembly simulation, primer design, CRISPR sgRNA design, and plasmid annotation. For protein-level sequence analysis use biopython or esm; for database lookups use gene-database or ensembl-database.
geo-database
Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.