agentmods.dev

database-lookup

database-lookup is a skill for Claude Code from K-Dense-AI/scientific-agent-skills. It costs 50 tokens per session (6,638 once invoked), scanned A, original, MIT.

A method for retrieving facts from documented public database APIs—interfaces that let software query named databases—with explicit filters, pagination, and source records.

In plain words
What is it for?
Use it to query public databases, retrieve complete filtered datasets, verify result counts, resolve identifiers, and record enough source information for someone else to repeat the lookup.
Why use it?
It helps produce repeatable, auditable lookups instead of relying on broad searches or guesses. This matters when small filtering differences can change scientific, regulatory, or financial results.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

not rated 50krepo +2.3k changed 14d ago A scan Socket: passSnyk: passSkillSpector: warn 50 tokens original MIT

Good fit Use it to query public databases, retrieve complete filtered datasets, verify result counts, resolve identifiers, and record enough source information for someone else to repeat the lookup.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/k-dense-ai/scientific-agent-skills/database-lookup
View source ↗ K-Dense-AI/scientific-agent-skills arxiv.org
About the project

Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.

K-Dense-AI/scientific-agent-skills · 50,453 stars · on GitHub · arxiv.org

Install

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.

Any agent
npx skills add K-Dense-AI/scientific-agent-skills --skill database-lookup
Clone the repo
git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills

Made for: Claude Code.

Wrote 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.

agentmods badge for database-lookup

README.md
[![agentmods](https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/database-lookup/github.svg)](https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/database-lookup)
Your own site
<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/database-lookup"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/database-lookup/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.

agentmods 80×15 button for database-lookup

Your own site · 80×15
<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/database-lookup"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/database-lookup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,638 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 2 Oct 2026
  • Snyk pass 2 Oct 2026
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 9 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Data Exfiltration · line 95
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 96
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 97
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 98
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 95
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 98
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 117
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 129
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 175
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00050 $0.06638
Opus 5.5 $0.00020 $0.02655
Sonnet 5.5 $0.00010 $0.01328
Haiku 4.5 $0.00005 $0.00664

Measured 14d ago against content hash ead247f62321, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

database-lookup scanned grade A with 1 finding 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 14d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

Use an available HTTP client for the required method and headers. A browsing tool may transform or truncate API payloads; use `curl` or a language HTTP client when exact JSON, pagination headers, or binary files matter.
Origin

Copies of this mod

3 near-identical copies found in the catalogue:

skills/database-lookup/SKILL.md · 400 lines

How it starts

The opening of the file, as written. The whole thing — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Database Lookup

This skill catalogs 80 databases with public, registered, or licensed 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/retrieval-contract.md before making API calls.

  4. 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.

  5. Make bounded API calls — See the Making API Calls section below. For exhaustive retrievals, count first when the API supports it, estimate cost, paginate or batch until retrieved counts reconcile, and fail visibly if the final dataset is incomplete. Ask for confirmation before a retrieval would exceed 10,000 records, 100 API calls, or the selected API's documented bulk-use guidance.

Read the full file on GitHub · 400 lines

Files

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.

Changes

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.

  1. 14d ago Changed · -6 lines scan B → A ead247f62321
  2. 15d ago Changed 20bf16e17f3a
  3. 1mo ago Changed · +2 lines dda99c6b4fbd
  4. 1mo ago Changed · +17 lines bda9257890f1
  5. 1mo ago First seen · 387 lines · 50 tokens per session scan B 3dfa2a009763

Subscribe to this mod's changes

database-lookup is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (50,453 stars, last pushed today), licensed MIT. It adds 50 tokens to every session and 6,638 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Researchai-scientistbioinformaticschemoinformaticsclaudeclaude-skillsclaudecode
Related

Other skills, from other repositories

discovery-toolbox

A routed repertoire of 90 scientific thinking operators for biological research agents - visual reasoning, detectability and information budgets, search reframing, causal identification, competing explanations, observation and selection processes, pipeline artifact diagnosis, effort allocation, and confirmation…

dekan-aleksandr/biodiscovery-skills · 122 tokens

discovery-director

Operate as a research director making original discoveries from a given biological question and dataset. Use when the task is open-ended scientific research, exploring omics or experimental data for findings, hypothesis generation and testing, screening a large candidate space of genes, variants, features or…

dekan-aleksandr/biodiscovery-skills · 114 tokens

create-video-seedance-2-fal

Generate a single 4-15s vertical video clip with ByteDance Seedance 2.0 reference-to-video via fal.ai. Multi-image reference (avatar + product + setting), native lip-synced VO + ambient audio (generate-audio on by default), internal multi-cut handling within one render. Routes through the GooseWorks FAL proxy (bills…

gooseworks-ai/goose-skills · 117 tokens

demo-builder

Builds personalized demo assets for top prospects using the founder's product API/MCP/SDK. Researches prospect, proposes demo concepts, builds working prototype, tests it, and generates comparison report with live demo link.

gooseworks-ai/goose-skills · 46 tokens

meta-ad-manager

Front door and loop owner of a Meta (Facebook/Instagram) ad harness. Reads the brand's ads/ docs, works out which campaign the user means and which stage it is at, hands off to the stage skill that runs it (intake, strategy, creative, launch, checks, fixes, answers), and writes every stage change back to the docs. Use…

gooseworks-ai/goose-skills · 108 tokens

inbound-lead-enrichment

Fills in missing data for inbound leads — researches the company, identifies the person's role and seniority, finds other stakeholders at the company, checks for existing CRM relationships, and updates the lead record. Produces enriched lead data ready for qualification or outreach. Tool-agnostic.

gooseworks-ai/goose-skills · 63 tokens