Structured Output

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

The annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true) provide basic safety signals. The description adds valuable behavioral context: it uses native CLI validation (not client-side), cost is ~$0.01-0.10/call and unaffected by schema complexity, and it is designed for machine-parseable output. These details go beyond what annotations convey.

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 concise: a lead sentence stating the core function, then a brief use case bullet, a cost note, and a tips section. Every sentence serves a purpose with no redundancy. The structure is front-loaded with the most important information.

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 has 9 parameters, no output schema, and moderate complexity, the description covers the essential aspects: purpose, use cases, cost, and parameter tips. It could mention default behavior (e.g., timeout default of 60000) or error handling, but the parameter schema covers most details. Overall, it is sufficiently complete for an agent to use correctly.

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?

All 9 parameters have descriptions in the schema (100% coverage), so baseline is 3. The description adds extra meaning: for the 'schema' parameter it notes 'Pass the JSON Schema as a JSON string' and 'Schema max size: 20KB'; for 'files' it explains 'include source text via the files parameter or inline in the prompt.' These tips improve parameter understanding beyond the schema alone.

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 'Generate JSON conforming to a provided JSON Schema' using a specific implementation (Claude CLI's --json-schema flag). It lists concrete use cases like data extraction, classification, and entity parsing, which distinguish it from sibling tools such as 'query' (likely free-form) and 'search' (retrieval).

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 explicitly says 'Use for: data extraction from text/files, classification, entity parsing, or any task needing machine-parseable output.' It also provides practical tips (schema max size, including source text via files parameter) but does not explicitly state when not to use this tool or mention alternatives beyond implying it's better than client-side validation.

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