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Report a correction

report_correction

Report a wrong fact about a brand or one of its relationships. Write what is wrong and what is right, in 10 to 2,000 characters. A person at Linty reads each correction.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "brand": "<brand>",
      "body": "<body>"
    },
    "name": "report_correction"
  }
}

Input Schema

NameRequiredDescriptionDefault
bodyYesWhat is wrong, and what is right.
brandYesA slug: lower-case letters, digits and hyphens, for example `acme-foods`.
relationshipNoA slug: lower-case letters, digits and hyphens, for example `acme-foods`.

Output Schema

NameRequiredDescriptionDefault
receivedYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already disclose non-read-only, non-destructive, non-idempotent behavior. The description adds meaningful context beyond that: a human at Linty reviews each correction, signaling asynchronous moderation rather than an immediate mutation. It stops short of stating expected turnaround or rejection behavior, so not a 5.

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?

Three short sentences, zero filler, purpose front-loaded before the content requirement and the review note. Every sentence 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?

With annotations and an output schema present, the description covers purpose, submission content, size bounds, and the review workflow. The optional relationship parameter is only gestured at ('or one of its relationships'), a minor gap.

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

Parameters3/5

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

Schema coverage is 100% and the schema already documents all three params including slug format and body content. The description's 'what is wrong and what is right' mirrors the body schema description, adding no new semantics, so the baseline of 3 applies.

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+resource: reporting an incorrect fact about a brand or relationship. This cleanly separates it from the read-only siblings (find_brands, get_brand, get_relationship) without needing 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 Guidelines3/5

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

It tells the agent what to submit ('what is wrong and what is right') and the size constraint, which is implicit guidance on valid use. It never states when to prefer this over alternatives or what happens if the fact is not actually wrong, so usage is implied rather than explicit.

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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