Katzilla MCP

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds valuable behavioral context beyond annotations: it discloses the data source ('NCBI PubChem (Public Domain)'), update frequency ('updates daily'), and details about the return format ('Katzilla envelope { data, quality, citation }') including quality scoring and citation components. This enriches the agent's understanding of the tool's behavior.

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 covers purpose, data fields, and search methods; the second covers source, updates, and return format. Every sentence adds essential information without redundancy, making it front-loaded 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?

Given the tool's moderate complexity (single parameter, read-only operation), rich annotations (covering safety and idempotency), and the presence of an output schema (implied by 'Returns the Katzilla envelope'), the description is complete. It explains the tool's scope, data source, update frequency, and return structure, leaving no significant gaps for the agent to understand its 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?

The input schema has 100% description coverage, with the single parameter 'name' fully documented in the schema. The description mentions 'Search by common name or CID', which adds slight semantic context about acceptable input types, but does not provide additional details beyond what the schema already states (e.g., examples like 'aspirin' are already in the schema). This meets the baseline for high schema coverage.

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 ('look up', 'search') and resources ('chemical compound data from NCBI PubChem'), listing exact data fields returned (molecular formula, weight, IUPAC name, etc.). It distinguishes itself from sibling tools by focusing specifically on PubChem compound data, unlike other health tools that cover different data sources like CDC, FDA, or clinical trials.

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 ('Look up chemical compound data from NCBI PubChem') and specifies search methods ('Search by common name or CID'), but does not explicitly state when not to use it or name specific alternative tools for similar queries. The context is sufficient for basic usage decisions.

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