AGR MCP Server

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

No annotations are provided, so the description carries the full burden. It mentions 'including human disease models and annotations', which adds some context about return content, but does not disclose behavioral traits such as rate limits, authentication needs, or whether it's a read-only operation. The description is minimal and lacks crucial operational details.

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 a single, efficient sentence that front-loads the core purpose ('Get disease associations for a gene') and adds specific details ('including human disease models and annotations') without unnecessary words. Every part earns its place, making it highly concise and well-structured.

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 moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but incomplete. It specifies the type of associations returned, which helps, but lacks details on output format, error handling, or usage constraints. Without annotations or output schema, more context would improve completeness for effective agent use.

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 description coverage is 100%, so the schema fully documents the parameters ('gene_id' and 'limit'). The description does not add any meaning beyond what the schema provides, such as format examples for 'gene_id' or clarification on 'limit' behavior. Baseline 3 is appropriate as the schema handles parameter documentation.

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 specific action ('Get disease associations') and resource ('for a gene'), and distinguishes it from siblings by specifying the type of associations ('including human disease models and annotations'), unlike tools like 'get_gene_phenotypes' or 'search_diseases' which focus on different data aspects.

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 when disease associations for a gene are needed, but does not explicitly state when to use this tool versus alternatives like 'search_diseases' or 'get_gene_phenotypes'. It provides basic context without exclusions or detailed guidance on tool selection.

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