format_json

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

Annotations declare readOnlyHint=true and openWorldHint=false, so the operation is safe and read-only. The description adds value by disclosing that it returns formatted output, a minified version, and stats, which goes beyond the annotations. It does not explicitly mention error handling for invalid JSON, but the 'validate' verb implies validation behavior, and the read-only annotation covers safety.

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 a single sentence that front-loads the core purpose ('Format, validate, and analyze JSON') and immediately lists the return values. It is concise with zero wasted words, and every phrase contributes to understanding the tool's functionality. Excellent structure for quick comprehension.

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?

For a tool with four straightforward parameters and no output schema, the description is largely complete. It explains what the tool does and what it returns, covering the key use cases. Minor gaps include explicit behavior on invalid JSON or how indent interacts with minify, but these are inferable from the schema and the stated purpose. Overall, sufficient for an agent to call it 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?

Schema description coverage is 100%, with all four parameters (input, indent, minify, sort_keys) well-documented in the schema. The description does not add meaningful detail beyond what the schema provides; it only hints at the output via 'formatted output' and 'minified version.' Since the schema fully covers parameter semantics, a baseline score of 3 is appropriate.

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: 'Format, validate, and analyze JSON.' It specifies the resource (JSON) and the three actions, and it distinguishes itself from sibling conversion tools (e.g., json_to_csv, json_to_xml) by focusing on formatting/validation/analysis rather than transformation. The mention of returning stats (key count, depth, size, type counts) further clarifies its scope.

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 contexts: when you need to format, validate, or analyze JSON. It does not explicitly exclude conversion tools, but the purpose is clear enough for an agent to infer when to use it. It lacks explicit exclusions or named alternatives, but given the sibling set, the intent is unambiguous.

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