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 context beyond annotations: it discloses the data source ('U.S. Consumer Product Safety Commission (Public Domain)'), update frequency ('updates daily'), and detailed return format ('Katzilla envelope { data, quality, citation }' with quality metrics and citation details). This significantly enhances behavioral understanding without contradicting 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 states purpose and filtering, the second provides source metadata and detailed return format. Every element adds value - no wasted words. It's appropriately front-loaded with the core functionality followed by important behavioral details.

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 filtering), rich annotations (four behavioral hints), 100% schema coverage, and existence of an output schema, the description provides excellent contextual completeness. It covers purpose, source, update frequency, and detailed return format - everything needed beyond what structured fields already provide. The output schema existence means the description doesn't need to explain return values in detail.

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 all four parameters well-documented in the input schema. The description mentions filtering 'by date range and product type' which aligns with startDate, endDate, and productType parameters, but adds no additional semantic context beyond what the schema already provides. The limit parameter isn't mentioned in the description at all. Baseline 3 is appropriate given complete 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 verb ('Search'), resource ('U.S. Consumer Product Safety Commission (CPSC) product recall data'), and scope ('Filter by date range and product type'). It distinguishes from sibling tools like 'consumer__cpsc-violations' and 'health__fda-recalls' by specifying CPSC as the source agency and product recalls as the focus.

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 U.S. Consumer Product Safety Commission (CPSC) product recall data') and mentions filtering capabilities. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling tools, though the CPSC focus implicitly distinguishes it from other recall tools like FDA or NHTSA recalls.

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