Katzilla MCP

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

The description adds valuable behavioral context beyond what annotations provide: it discloses the return format ('Katzilla envelope { data, quality, citation }'), explains what quality scores represent ('freshness/uptime/confidence'), describes citation contents ('source URL, license, SHA-256 data hash'), and mentions update frequency ('updates annual'). This complements the annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) without contradicting them.

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 establishes purpose and scope, the second details the return format and behavioral aspects. Every element serves a purpose with zero wasted words, making it easy to parse while being information-dense.

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 (data querying with quality metrics), rich annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint), 100% schema coverage, and existence of an output schema, the description provides excellent contextual completeness. It explains the return structure, quality scoring, citation details, and update frequency—exactly what's needed beyond the structured fields.

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?

With 100% schema description coverage, the input schema already fully documents both parameters. The description doesn't add any additional parameter semantics beyond what's in the schema descriptions, so it meets the baseline of 3. It doesn't compensate for gaps because there are none to compensate for.

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 ('Query', 'Retrieve') and resources ('U.S. Census Bureau American Community Survey (ACS) 5-year estimates', 'population, income, housing, and demographic variables by geography'). It distinguishes itself from sibling tools like 'demographics__census-economic-indicators' by focusing specifically on ACS data rather than other census datasets.

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 context through the mention of 'Demographics & Population Agent' and specifying ACS 5-year estimates, but doesn't explicitly state when to use this tool versus alternatives like 'demographics__census-economic-indicators' or other demographic tools. No explicit exclusions or prerequisites are provided.

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