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Get the fix for a check on a given platform

explain_fix
Read-onlyIdempotent

Returns the fix text for one check id (from list_checks or a report) written for a platform: shopify, wordpress, magento, framer, webflow, wix, squarespace, bigcommerce, hubspot, nextjs or generic. No usage limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
check_idYesCheck id, for example ai_bots, product_schema, llms_txt
platformNoPlatform key or CMS name; defaults to generic

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint and idempotentHint, so safety and repeatability are covered. The description adds one genuinely useful behavioral fact beyond them — 'No usage limit' — which matters for agents deciding to call it repeatedly, but it says nothing about return format, error behavior, or unknown platform handling.

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?

Two dense sentences with no filler; the core action and its scope lead, and the platform list plus the no-limit note follow. Every clause earns its place.

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 two-parameter read tool with no output schema, the description covers what is returned ('fix text'), the keying (one check id), the platform dimension, and rate-limit behavior. Only minor gaps remain around failure modes and output shape.

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% so the baseline is 3, but the description goes further by enumerating the accepted platform values (shopify, wordpress, magento, framer, webflow, wix, squarespace, bigcommerce, hubspot, nextjs, generic), which the schema leaves as an unenumerated 'platform key or CMS name'. That enumeration is real added value.

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

Purpose5/5

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

States a specific verb (returns), resource (fix text for one check id), and scope (per-platform). It is clearly differentiated from siblings such as list_checks (which enumerates checks) and get_report (which returns the report), so an agent can pick this without opening any schema.

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

Usage Guidelines4/5

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

Explicitly tells the agent where the check_id comes from — 'from list_checks or a report' — which routes it from sibling tools. It lacks an explicit when-not condition (e.g. what to do if the check id is unknown or the platform is unsupported), but the context is clear.

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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