database-lookup

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Query documented public database APIs with explicit endpoints, filters, pagination, and provenance. Use when a scientific, regulatory, financial, or other database-backed fact must be retrieved reproducibly from a named source rather than inferred from general knowledge.

API & Backend 31,883 stars 3168 forks Updated today MIT

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Skill Content

# Database Lookup This skill catalogs 78 public databases with documented API access patterns. Your job is to turn the user's intent into a reproducible retrieval: select the authoritative database(s), make bounded 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 1. **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. 2. **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. 3. **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) and `references/ret...

Details

Author
K-Dense-AI
Repository
K-Dense-AI/scientific-agent-skills
Created
9 months ago
Last Updated
today
Language
Python
License
MIT

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