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explain_check

Explains what a specific AI-search readiness check evaluates, helping you understand its evidence and apply fixes.

Instructions

Explain what one of the 20 elements (e01_title ... e20_blog) looks for.

Input Schema

NameRequiredDescriptionDefault
checkYesElement id, e.g. e07_faq_schema

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full disclosure burden, yet it says nothing about whether this is read-only, what form the explanation takes (prose vs structured), or how a bad element id is handled. The only behavioral hint is the finite set of 20 elements, which does imply a bounded, non-mutating lookup.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler; the verb, the resource, and the valid identifier space all appear immediately.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter, non-destructive lookup with no output schema, the definition covers what is needed to invoke it correctly. Minor gaps are the unexplained return format and the drift between "check" in the name/parameter and "element" in the description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with an example id, and the description still adds value by disclosing the full domain: exactly 20 elements, ranging from e01_title to e20_blog. That count and range tell the agent which ids are valid, beyond the single schema example.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description pairs a specific verb ("Explain") with a bounded resource (one of the 20 elements) and enumerates the ID space, so the agent knows exactly what it gets back. It never mentions the sibling audit_page, so the distinction between 'explain a check' and 'run the audit' is left to inference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: an agent can gather that this is for learning what a check tests, presumably before or after running audit_page. There is no explicit when-to-use statement, no exclusion, and no mention of the alternative tool by name.

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

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