Pythia MCP

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

With no annotations provided, the description carries full burden but lacks critical behavioral details. It mentions fetching 'latest' data but doesn't define what 'latest' means (e.g., most recent publication, update timestamp). It doesn't disclose rate limits, authentication needs, data freshness guarantees, or potential data volume/format. The description adds minimal context beyond the basic fetch operation.

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 efficiently structured in two sentences: first states the action and sources, second specifies the return content. It's appropriately sized for the tool's complexity, though could potentially be more front-loaded by integrating return details into the first sentence.

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 data-fetching tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It lacks behavioral transparency (rate limits, auth, freshness), doesn't explain the relationship between parameters, and provides no output format details. The description should compensate for missing structured data but doesn't adequately do so.

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%, providing clear parameter documentation. The description adds no parameter-specific semantics beyond what's in the schema (e.g., doesn't explain how 'channel' interacts with 'collaboration', or default behavior when parameters are omitted). Baseline 3 is appropriate since the schema does the heavy lifting.

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 action ('Fetch'), resources ('Higgs boson measurement data from both HEPData and CERN Open Data portals'), and output content ('signal strength measurements, coupling measurements, and analysis results'). It distinguishes from siblings like 'fetch_hepdata_record' and 'get_cern_opendata_record' by specifying it fetches from both sources and focuses on latest Higgs data, but doesn't explicitly contrast with 'search_hepdata' or 'search_cern_opendata'.

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 no guidance on when to use this tool versus alternatives like 'fetch_hepdata_record', 'get_cern_opendata_record', 'search_hepdata', or 'search_cern_opendata'. It mentions fetching from both portals but doesn't clarify if this is for consolidated latest data versus specific searches or individual portal access.

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