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

Annotations already establish readOnly/idempotent/non-destructive, and the description goes well beyond them: it reports only the FIRST error with exact line and column, emits duplicate-key warnings and structure stats, guarantees formatting never changes a value, and preserves big-number precision. This is substantive behavioral disclosure an agent cannot get from the 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?

Two sentences, both dense with distinct information: sentence one covers validation outputs and formatting guarantees, sentence two covers when to reach for the tool. Nothing is redundant with the title or annotations and the usage cue is front-loaded at the end as a clear call to action.

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?

With no output schema, the description correctly carries the burden of describing return content (error position, explanation, warnings, stats). The only gap is the undocumented sort_keys parameter, which affects output ordering and is not mentioned anywhere.

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 coverage is 50% (text and sort_keys carry no descriptions). The description clarifies the effect of formatting (pretty-print vs minify, value preservation, precision) which maps to format/indent, but it never explains sort_keys or that indent only applies when format is true, so it only partly compensates for the coverage gap.

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 states a specific verb+resource pair (strictly validate JSON) and details the exact outputs (first error line/column, explanation, duplicate-key warnings, structure stats), plus optional formatting. No sibling tool (count_text, diff_text, generate_qr) overlaps with JSON validation, so the boundary is unambiguous.

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?

It gives explicit triggering conditions: 'Use this before claiming JSON is valid or when locating a syntax error in long JSON.' That is clear when-to-use guidance. It stops short of naming when NOT to use it or pointing to an alternative, but no plausible alternative exists among the siblings.

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