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, covering safety and idempotency. The description adds valuable context beyond annotations: it specifies the return format ('Katzilla envelope { data, quality, citation }'), explains quality metrics ('freshness/uptime/confidence'), and details citation components ('source URL, license, and a SHA-256 data hash for audit'). It also notes data update frequency ('updates annual'), which is not covered by annotations.

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 and scope, the second details the return format and metadata. Every sentence adds value (data source, return structure, quality metrics, citation details) with no redundant or vague language. It is appropriately sized and front-loaded with 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 complexity (simple read-only query 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 like data source, update frequency, and return format details, compensating adequately where structured fields might not fully inform the agent.

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 clear descriptions for both parameters (state and limit). The description does not add any parameter-specific semantics beyond what the schema provides (e.g., no extra details on state codes or limit behavior). According to the rules, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description.

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: retrieving 'water quality assessment data from EPA ATTAINS' with specific details like 'impaired waters, pollutant sources, and cleanup status by state' and that it 'Tracks which waterways meet Clean Water Act standards.' It distinguishes from siblings by specifying the data source (EPA ATTAINS) and type (water quality), unlike other environment tools like EPA AQS (air quality) or NOAA CDO (climate data).

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 for water quality data by state, but does not explicitly state when to use this tool versus alternatives (e.g., other EPA tools like epa-aqs for air quality). It mentions the data source and update frequency ('updates annual'), which provides some context, but lacks explicit guidance on prerequisites, exclusions, or comparisons to sibling tools.

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