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

With no annotations, the description carries the full burden and does disclose meaningful behavior: it is deterministic, returns JSON only, and requires payment of $0.035 USDC per call via x402 — cost/auth context an agent genuinely needs. It stops short of describing error behavior or limits on input size.

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?

Three short sentences, front-loaded with the purpose and ending with output format and cost. Almost every clause earns its place; only 'Returns JSON only' partly overlaps with the schema-driven expectation of a structured result.

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 single-input, no-output-schema tool, the description covers purpose, detection scope, return format and payment. It is nearly complete, though it omits how the findings are structured in the returned JSON.

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?

Only one parameter, fully documented in the schema ('Any JSON value to inspect') at 100% coverage. The description adds no format or size constraints beyond the schema, so the baseline 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?

States a specific verb+resource ('Deterministic JSON/data-quality inspection') and enumerates the exact findings it produces: null-heavy fields, duplicate array items, shape inconsistencies and structural statistics. This lets an agent distinguish it from siblings like schema-drift-guard and text-quality-gate without opening a schema.

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 ('for autonomous agents') and what the tool detects, but never states when to prefer it over the adjacent schema-drift-guard or text-quality-gate tools, nor any preconditions. Usage is implied rather than directed.

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