Search the MeSH vocabulary for standardized medical terms.
Find MeSH (Medical Subject Headings) descriptors to use in
precise PubMed searches. Returns MeSH IDs, preferred terms,
and scope notes.
Args:
term: Search term (e.g. 'diabetes', 'heart failure', 'opioid').
limit: Maximum results (default 10).
| Name | Required | Description | Default |
|---|---|---|---|
| term | Yes | ||
| limit | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must fully disclose behavior. It states the tool returns MeSH IDs, preferred terms, and scope notes, which is adequate for a search tool. However, it does not mention any potential rate limits, case sensitivity, or pagination, leaving some behavioral traits unspecified.
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 concise, using three effective sentences plus an Args section. No redundant words, and the structure is logical: purpose, elaboration, then parameter details. It is front-loaded with the core action.
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 low complexity (2 params, no nested objects) and existence of an output schema, the description adequately covers the tool's purpose, parameters, and return values. It does not elaborate on edge cases or advanced usage, but that is acceptable for a focused search tool.
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?
Schema coverage is 0%, so the description must compensate. It provides clear, human-readable explanations for both parameters: term with examples ('diabetes', 'heart failure') and limit with default value. This adds significant meaning beyond the basic schema types.
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 explicitly states the tool searches the MeSH vocabulary for standardized medical terms, with a clear verb+resource combination. It distinguishes itself from siblings like search_pubmed by focusing on vocabulary retrieval rather than article searches.
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 explains that MeSH descriptors found are for use in precise PubMed searches, providing context. However, it does not explicitly state when not to use it or compare with alternatives, so it is slightly lacking in guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.