Pythia MCP

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

No annotations are provided, so the description carries full burden. It mentions what information is returned but doesn't disclose behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, error conditions, or response format. For a tool with no annotations, this leaves significant gaps in understanding how it behaves.

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 purpose and key details. Every word earns its place, with no redundant information or fluff, making it easy to parse quickly.

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 no annotations and no output schema, the description provides basic purpose and return content but lacks completeness for a tool that likely returns complex data. It doesn't cover behavioral aspects, error handling, or output structure, which are important for an agent to use it correctly in this context.

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%, with the parameter 'datasetPath' fully documented in the schema. The description doesn't add any parameter-specific semantics beyond what the schema provides (e.g., it doesn't explain path formats or constraints further). Baseline 3 is appropriate since 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 verb 'Get' and the resource 'detailed information about a specific experimental dataset', specifying what information is included (best-fit values, uncertainties, and correlations). It distinguishes from siblings like 'list_experimental_data' (which likely lists datasets) and 'fetch_hepdata_record' (which might fetch raw data), but doesn't explicitly name alternatives.

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 detailed dataset information is needed, but doesn't explicitly state when to use this tool versus alternatives like 'fetch_hepdata_record' or 'get_latest_higgs_data'. It provides some context by specifying 'experimental dataset', but lacks clear exclusions or named alternatives.

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