Katzilla MCP

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

Annotations already cover read-only, non-destructive, idempotent, and open-world hints. The description adds valuable behavioral context beyond annotations: it specifies the source (SHARE/OSF with CC-BY 4.0 license), update frequency (daily), and details about the return format (Katzilla envelope with quality scores and citation data including SHA-256 hash). This enriches understanding of data freshness, licensing, and auditability.

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: the first states purpose and source, the second details return format and audit features. Every phrase adds value without redundancy, and it is front-loaded with the core functionality.

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 (search with two parameters), rich annotations (covering safety and idempotency), and the presence of an output schema (implied by 'Returns the Katzilla envelope'), the description is complete. It adds necessary context about the data source, update frequency, and return structure that complements the structured fields effectively.

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 both parameters (query, limit) well-documented in the schema. The description does not add any parameter-specific semantics beyond what the schema provides, such as query syntax examples or limit implications. Baseline 3 is appropriate since the schema carries the full parameter documentation burden.

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 tool's purpose with specific verbs ('search the SHARE database') and resources ('research outputs including papers, datasets, and preprints'). It distinguishes from sibling tools by specifying the unique SHARE/OSF source and daily updates, unlike other science tools like arXiv or PubMed that search different repositories.

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 when to use this tool ('search the SHARE database for research outputs'), but does not explicitly state when not to use it or name alternatives among the many sibling tools. It implies usage for SHARE-hosted content but lacks explicit exclusions or comparisons.

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