BioPython MCP Server

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 effectively describes key traits: rate limits ('3 req/sec or 10 req/sec with API key'), caching behavior ('Cached results have 1 hour TTL'), and output structure ('Returns full abstracts when available'), providing comprehensive behavioral context beyond basic functionality.

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 clear sections (Args, Returns, Examples, Notes), front-loading the core purpose. Each sentence adds value, such as explaining enriched metadata, parameter details, and behavioral notes, with no wasted content, making it efficient and easy to parse.

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?

For a tool with 6 parameters, no annotations, and an output schema, the description is complete. It covers input semantics, behavioral traits (rate limits, caching), output structure, and usage examples, providing all necessary context for an agent to invoke the tool correctly without relying on external documentation.

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?

Given a schema description coverage of 0%, the description compensates fully by detailing all 6 parameters in the 'Args' section, including defaults, syntax examples (e.g., 'PubMed search query (supports all Entrez query syntax)'), and practical usage. This adds significant meaning beyond the bare schema, ensuring parameters are well-understood.

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's purpose as 'Search PubMed with enhanced metadata extraction' and 'provides enriched PubMed search results with structured article metadata,' which is a specific verb+resource combination. It clearly distinguishes from sibling tools like 'search_pubmed' by emphasizing metadata enrichment and structured output, avoiding tautology.

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 provides clear context for usage through examples and notes, such as 'Uses comprehensive Entrez query syntax' and 'Rate limited (3 req/sec or 10 req/sec with API key).' However, it does not explicitly state when to use this tool versus alternatives like 'search_pubmed' or 'entrez_search,' missing direct sibling differentiation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.