/pubmed_database

name: pubmed-database
description: >-
  Search PubMed for scientific literature, including published clinical trials.
  Fetch abstracts and full text. Link published research to biological databases
  (gene, protein, nucleotide, PubChem) to discover associations between papers
  and specific compounds or genes. Verify medical spelling, match raw citations,
  and cache result sets for bulk processing. Interfaces NCBI E-utilities and PMC
  BioC APIs.

PubMed API

Prerequisites

1. **`uv`**: Read the `uv` skill and follow its Setup instructions to ensure `uv` is installed and on PATH. 2. **User Notification**: If .licenses/pubmed_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://pubmed.ncbi.nlm.nih.gov/disclaimer/ and https://www.ncbi.nlm.nih.gov/home/about/policies/ and to always check the license of the papers retrieved by the skill for any restrictions, then (2) create the file recording the notification text and timestamp. 3. **`.env` file**: Make sure the `.env` file exists in your home directory. Create one if it does not exist. 4. **`NCBI_API_KEY`** (optional): Raises the NCBI E-utilities rate limit from 3 to 10 requests/second. The skill works without it, but a key is recommended if the user plans many queries or encounters a 429 error. You can register for a key for free at https://www.ncbi.nlm.nih.gov/account/settings/. You **MUST** use the safe credentials protocol in the `credentials` skill to check for and request this key if this skill looks relevant to the user's request. 5. **`USER_EMAIL`** (optional): Identifies the caller to NCBI (recommended by their Terms of Use). You **MUST** use the safe credentials protocol in the `credentials` skill to check for and request this credential if this skill looks relevant to the user's request.

This skill provides CLI access to the NCBI PubMed and PubMed Central APIs via `scripts/pubmed_api.py` — a single CLI with 10 functions covering search, fetch, linking, full text, spelling, discovery, citation matching, and caching.

Core Rules

• **API Use**: Always use the provided wrapper `scripts/pubmed_api.py` which

manages rate limits automatically and prevents API abuse. Setting the `NCBI_API_KEY` environment variable raises the rate limit from 3 to 10 requests/second. Querying the API any other way (e.g. via curl, wget, or hand-written code) is strictly forbidden.

• **JSON Processing**: Use `jq` to filter and transform JSON output (or python

equivalents if `jq` is not available) to prevent hallucinations and context overflow.

• **Temporary Files**: To avoid polluting the working directory with JSON

files, use a temporary directory inside the current directory. When running multiple agents or tasks in parallel, ensure each uses a unique subdirectory name (e.g., `tmp_$TASK_ID/`) to avoid file collisions.

• **Notification**: If this skill is used, ensure this is mentioned in the

output AND list the URLs of all papers that were used in producing the output.

Structure of the skill folder

• `SKILL.md` - This file
• `scripts/pubmed_api.py` - The skill CLI
• `references/` - Directory with detailed function specifications
• `advanced-linking.md`
• `advanced-search.md`
• `bulk-workflows.md`
• `citation-matching.md`
• `cross-database-linking.md`
• `fetch-and-resolve.md`
• `search-and-discovery.md`
• `utilities.md`

CLI Usage

uv run scripts/pubmed_api.py <output_file> <function_name> <required_args> [--flag value ...]

• **Positional Arguments**: Arguments are positional; list arguments are

passed as comma-separated strings without spaces (e.g. `"35113657,31234568"`).

• **Flag Options**: Optional arguments can be passed as `--flag value` instead

of positional args.

• **Output Handling**: On success, JSON is written to `output_file`. On error,

the process exits with a non-zero code and no output file is written.

Example Usage

uv run scripts/pubmed_api.py ./search_results.json search_pubmed "BRCA1" --max_results 5
cat ./search_results.json | jq '.[]' -r
uv run scripts/pubmed_api.py ./abstracts.json fetch_article_abstracts "35113657"
cat ./abstracts.json | jq '.[0].title' -r

Essential Recipes

**Join PMIDs for the next call (most common chaining pattern):**

cat ./search_results.json | jq -r 'join(",")'

**Slim abstracts to essential fields and truncate long abstracts:**

cat ./abstracts.json | jq '[.[] | {pmid, title, snippet: (.abstract // "")[:500]}]'

**Filter by keyword (null-safe):**

cat ./abstracts.json | jq '[.[] | select((.title // "") | contains("Review"))]'

Context Management & Accuracy

When processing larger result sets (>10 abstracts):

1. **Filter Early**: Use `jq` to verify keywords in abstracts *before* reading the full JSON into context. 2. **Slimming**: Extract only `title` and `abstract` fields unless explicitly instructed otherwise. Author lists and metadata contribute to noise. 3. **Bulk Operations (N > 10)**: Avoid fetching or processing IDs one-by-one. The API and History Server are designed for bulk retrieval. Fetch all data in a **single turn** and use shell pipelines to slim the results before reading into context. This prevents turn exhaustion and context overflow. 4. **Grounding**: Never use internal knowledge to provide specific identifiers (PMIDs, CIDs, Gene IDs) if no results are found. Report the tool's output accurately to ensure results are grounded in the current database state. 5. **Search Termination**: When asked to find papers that may not exist, limit exploration to 3–5 high-quality, varied search queries. If no results match after these attempts, conclude that no papers meet the criteria r