fda-database

fda-database is a skill for Claude Code, Codex from Zaoqu-Liu/ScienceClaw. It costs 43 tokens per session (3,615 once invoked), scanned A, a copy of fda-database, MIT.

A way to query openFDA, the US Food and Drug Administration's public data service. It covers medicines, medical devices, foods, veterinary products, substances, recalls, safety reports, and regulatory submissions.

In plain words
What is it for?
Use it to investigate adverse events, approvals, recalls, drug shortages, device clearances, product labels, and chemical or substance identifiers.
Why use it?
It brings FDA records into repeatable data queries instead of requiring manual searches across separate public pages. This helps compare and analyse regulatory and safety information.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Not installable on its own: it runs a file from its repository that does not travel with it. Clone the repository, or install whatever ships that file. The line is python scripts/fda_examples.py.

Install

Getting it into your agent

There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.

Made for: Claude Code, Codex.

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 fda-database

README.md
[![agentmods](https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/fda-database.svg)](https://agentmods.dev/skills/zaoqu-liu/scienceclaw/fda-database)
Your own site
<a href="https://agentmods.dev/skills/zaoqu-liu/scienceclaw/fda-database"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/fda-database.svg" alt="Measured on agentmods" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,615 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 86% copy Near-identical to another mod 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 $0.00043 $0.03615
Opus 5 $0.00022 $0.01808
Sonnet 5 $0.00009 $0.00723
Haiku 4.5 $0.00004 $0.00362

Measured 2d ago against content hash 953adcd5e9ba, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

fda-database 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 2d 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.

Origin

This is a copy

86% identical to fda-database — 6 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.

skills/fda-database/SKILL.md · 518 lines

How it starts

The opening of the file, as written. The whole thing — 518 lines — stays where its author put it; the contents beside it link to each section on GitHub.

FDA Database Access

Overview

Access comprehensive FDA regulatory data through openFDA, the FDA's initiative to provide open APIs for public datasets. Query information about drugs, medical devices, foods, animal/veterinary products, and substances using Python with standardized interfaces.

Key capabilities:

  • Query adverse events for drugs, devices, foods, and veterinary products
  • Access product labeling, approvals, and regulatory submissions
  • Monitor recalls and enforcement actions
  • Look up National Drug Codes (NDC) and substance identifiers (UNII)
  • Analyze device classifications and clearances (510k, PMA)
  • Track drug shortages and supply issues
  • Research chemical structures and substance relationships

When to Use This Skill

This skill should be used when working with:

  • Drug research: Safety profiles, adverse events, labeling, approvals, shortages
  • Medical device surveillance: Adverse events, recalls, 510(k) clearances, PMA approvals
  • Food safety: Recalls, allergen tracking, adverse events, dietary supplements
  • Veterinary medicine: Animal drug adverse events by species and breed
  • Chemical/substance data: UNII lookup, CAS number mapping, molecular structures
  • Regulatory analysis: Approval pathways, enforcement actions, compliance tracking
  • Pharmacovigilance: Post-market surveillance, safety signal detection
  • Scientific research: Drug interactions, comparative safety, epidemiological studies

Quick Start

1. Basic Setup

from scripts.fda_query import FDAQuery

# Initialize (API key optional but recommended)
fda = FDAQuery(api_key="YOUR_API_KEY")

# Query drug adverse events
events = fda.query_drug_events("aspirin", limit=100)

# Get drug labeling
label = fda.query_drug_label("Lipitor", brand=True)

# Search device recalls
recalls = fda.query("device", "enforcement",
                   search="classification:Class+I",
                   limit=50)

2. API Key Setup

While the API works without a key, registering provides higher rate limits:

  • Without key: 240 requests/min, 1,000/day
  • With key: 240 requests/min, 120,000/day

Read the full file on GitHub · 518 lines

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. 2d ago First seen · 518 lines · 43 tokens per session scan A 953adcd5e9ba

Subscribe to this mod's changes

fda-database is a skill published in the GitHub repository Zaoqu-Liu/ScienceClaw (60 stars, last pushed 5mo ago), licensed MIT. It adds 43 tokens to every session and 3,615 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to fda-database, differing in 6 lines, and is treated as a copy.

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