Find articles that cite a given PubMed article.
Useful for tracking the impact and follow-up research of a
key publication.
Args:
pmid: PubMed ID of the article to find citations for.
limit: Maximum citing articles to return (default 20, max 100).
| Name | Required | Description | Default |
|---|---|---|---|
| pmid | Yes | ||
| limit | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool returns citing articles and documents the default and maximum limit. However, it does not specify behavior for edge cases (e.g., no citations found, empty results) or any constraints like rate limits or data freshness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with an Args section listing parameters. The first sentence is clear and direct. The second sentence ('Useful for tracking...') adds context but is slightly verbose; removing it would improve conciseness without loss of essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (two parameters, one required), the description is adequate. The presence of an output schema means return values do not need to be detailed here. However, it could be more complete by explicitly stating that results are a list of articles or brief summary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds significant meaning beyond the input schema: it explains pmid as 'PubMed ID of the article to find citations for' and limit with its default (20) and maximum (100). Since schema description coverage is 0%, the description fully compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Find articles that cite a given PubMed article.' This is a specific verb-resource pair that distinguishes it from siblings like find_related_articles (which finds related articles, not citing ones) and get_article_detail (which retrieves detail for a specific article).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for tracking impact and follow-up research, but does not explicitly state when to use this tool versus alternatives (e.g., find_related_articles for related articles, or search_pubmed for general searches). No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose with no overlap: find_related_articles finds similar papers, get_article_detail retrieves metadata, get_cited_by finds citations, search_mesh searches vocabulary, and search_pubmed performs general searches. The descriptions reinforce these distinct roles, making misselection unlikely.
All tools follow a consistent verb_noun pattern with snake_case (e.g., find_related_articles, get_article_detail, search_pubmed). The naming is predictable and readable throughout, with no deviations in style or convention.
With 5 tools, the server is well-scoped for literature search and retrieval. Each tool earns its place by covering key workflows: searching, retrieving details, finding related/citing articles, and vocabulary support. This count is neither too sparse nor bloated for the domain.
The toolset covers core PubMed operations effectively: search, retrieve details, find related/citing articles, and vocabulary lookup. A minor gap is the lack of tools for advanced filtering (e.g., by date range or journal) or batch operations, but agents can work around this with query syntax.