Agent skill · Documentation

tac2017-adr

Query TAC 2017 ADR annotated drug labels for adverse drug reactions. Use whenever the user asks about ADRs extracted from FDA drug labels, MedDRA-normalized adverse reactions, or wants to look up a drug name, ADR string, or MedDRA code in the TAC 2017 ADR corpus.

BioTender-maxgithub.com/BioTender-maxGitHub ↗
claude-codeships scriptsNOASSERTION
Install
npx skills add BioTender-max/awesome-bio-agent-skills --skill tac2017 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 6
SKILL.md size: 3 KB
Bundled scripts: yes
Path: skills/drugclaw/tac2017/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 135
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# TAC 2017 ADR Query Skill Search 200 FDA drug labels annotated with adverse reactions, severity, and MedDRA normalization from the TAC 2017 shared task. ## Entity Auto-detection | Input Pattern | Detected As | Match Logic | |---|---|---| | `10019211` (8 digits) | MedDRA ID | exact on `meddra_pt_id` or `meddra_llt_id` | | `ACTEMRA` (known drug) | Drug name | exact (case-insensitive) on drug label name | | `headache` (known ADR) | ADR string | exact on ADR reaction string | | anything else | Free text | substring on drug names, ADR strings, MedDRA PT/LLT names | ## API | Function | Input | Returns | |---|---|---| | `search(entity)` | single entity string | `list[dict]` — matching label hit(s) | | `search_batch(entities)` | list of entity strings | `dict[str, list[dict]]` | | `summarize(hits, entity)` | hit list + query label | compact LLM-readable text | | `to_json(hits)` | hit list | `list[dict]` (JSON-serializable) | | `list_drugs()` | — | sorted list of all drug names | | `stats()` | — | dataset-level statistics dict | ## Hit Dict Structure Each hit returned by `search()` contains: | Field | Type | Description | |---|---|---| | `drug` | str | Drug label name | | `source_file` | s

What's inside
Steps it walks through
  1. Entity Auto-detection
  2. API
  3. Hit Dict Structure
  4. Usage
  5. Data
Ships with 5 files
  • README.md
  • __init__.py
  • example.py
  • retrieve.py
  • tac2017_skill.py
More from awesome-bio-agent-skills
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About this skill
What does the tac2017-adr skill do?

Query TAC 2017 ADR annotated drug labels for adverse drug reactions. Use whenever the user asks about ADRs extracted from FDA drug labels, MedDRA-normalized adverse reactions, or wants to look up a drug name, ADR string, or MedDRA code in the TAC 2017 ADR corpus.

How do I install it?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill tac2017 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going