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KyleVick4

ryogena-pubmed-mcp

by KyleVick4

search_pubmed

Search PubMed literature and retrieve key metadata like title, authors, journal, publication date, and DOI for each result, with adjustable result count and sorting by relevance, date, or citation count.

Instructions

Search PubMed and return slim metadata for each hit.

Two-step under the hood: esearch gets PMIDs, esummary gets title/authors/journal/pubdate/DOI for each. Use fetch_article next when you need the full abstract for a specific result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoSort order: 'relevance' (default), 'pub_date' (newest first), or 'most_cited' (proxy via NCBI ranking).relevance
queryYesPubMed query — free text or full PubMed query syntax. Examples: 'JAK2 inhibitor selectivity', 'CRISPR base editing[TI] AND 2024[DP]'.
max_resultsNoMax PMIDs to return. Default 20, hard cap 100.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description carries full burden. It reveals the two-step process (esearch + esummary) and the specific metadata fields returned (title, authors, journal, pubdate, DOI). It does not disclose rate limits, authentication needs, or whether the tool is read-only, but for a public database search, the implied read-only nature is acceptable. The description adds value beyond annotations (which are absent) by explaining internal behavior and output scope.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, each with a distinct purpose: purpose, internal process, next-step advice. No wasted words, front-loaded with the core action. Every sentence is informative and earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema (not shown here but flagged as present), the description does not need to detail return structure. It already lists the key fields. The tool has three parameters, all documented in schema, and the description covers the overall behavior, internal steps, and follow-up tool. This is complete for a search tool with clear sibling relationships.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%: all three parameters have clear descriptions in the input schema. The tool description does not add further detail about parameter meaning (e.g., accepted query syntax is mentioned only in schema, not in description). Baseline is 3 because the schema already documents parameters well; the description provides no additional semantic value for parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Search PubMed and return slim metadata for each hit', which is a specific verb-resource combination. It distinguishes from the sibling 'fetch_article' by explicitly noting that tool is for full abstracts. The two-step internal process (esearch + esummary) is also mentioned, providing clarity on what 'slim metadata' means.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit guidance on when to use the sibling 'fetch_article' ('Use fetch_article next when you need the full abstract'). This helps the agent choose the correct tool. However, it does not address other siblings like 'find_related' or 'search_by_author', leaving some gaps in when-not-to-use this tool.

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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