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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, a site report or a product page report) written for a platform: shopify, wordpress, magento, framer, webflow, wix, squarespace, bigcommerce, hubspot, nextjs or generic. No usage limit.

Input 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

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds one genuinely extra trait, 'No usage limit', which is useful rate-limit context, but it says nothing about what happens when a check has no platform-specific fix or when an invalid platform key is passed.

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

Conciseness4/5

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

A single tight sentence with the return value front-loaded and the platform enumeration in a compact parenthetical. The eleven-item list is long but each item is load-bearing since the schema provides no enum; only minor density cost.

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 full schema coverage and read-only annotations, the description covers purpose, input sources, and platform domain. The only meaningful gap is the absence of any note on missing/unsupported fix text, which matters because this tool has no output schema to reveal that behavior.

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 would be 3, but the description earns extra credit by enumerating the eleven accepted platform values (shopify, wordpress, magento, framer, webflow, wix, squarespace, bigcommerce, hubspot, nextjs, generic) where the schema has no enum and only says 'Platform key or CMS name; defaults to generic'. That enumeration is real added value for correct invocation.

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 and resource ('Returns the fix text for one check id') and scopes it to the platform dimension, which is exactly what distinguishes it from siblings like get_report and audit_site. An agent can tell what it produces without opening the 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 a valid check_id comes from ('from list_checks, a site report or a product page report'), which is the key prerequisite and routing signal. It stops short of stating when NOT to use it or naming a competing tool for fix retrieval, so it is clear context rather than full when/when-not guidance.

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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