Cleotic

Get reputation

get_reputation

Read-onlyIdempotent

What AI answers claim about the brand: open narratives (repeated claims grouped into one story) with severity, state, the engines carrying each as "k of n" answers, first sighting, a quote, the confirmed fact it contradicts and the top cited source, plus exposure: how many answers naming the brand carried a risky claim. Strengths are listed apart. Use get_narrative for one narrative's answers.

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>"
    },
    "name": "get_reputation"
  }
}

Input Schema

Name	Required	Description	Default
`brand`	Yes	Brand or study: its ID from list_brands, or its name (exact or a unique prefix).

Output Schema

Name	Required	Description
`data`	Yes
`generated_at`	Yes	RFC 3339 time the response was made.
`schema_version`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 31, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already establish that this is a read-only, idempotent, non-destructive operation. The description adds useful context about the returned reputation data, including narrative severity/state, engine coverage as 'k of n' answers, first sighting, quotes, contradicted facts, top cited sources, exposure counts, and separated strengths.

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?

The description is front-loaded with the core resource and then enumerates the important return fields. It is dense and somewhat list-heavy, but every sentence carries useful information and there is no wasted text.

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?

Given the single required parameter, rich input schema, annotations, and presence of an output schema, the description is largely complete. Its main gap is not explaining when to choose this tool over other reputation-adjacent siblings beyond get_narrative.

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?

The schema fully documents the single brand parameter, including ID/name/prefix behavior, so the description need not repeat that. The description does not add any parameter formatting or selection guidance beyond what the schema already provides.

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 clearly states that the tool surfaces what AI answers claim about a brand, specifically open narratives with severity, state, engine counts, sightings, quotes, contradicted facts, cited sources, and exposure. It also distinguishes itself from get_narrative, though it uses a noun phrase rather than a direct verb-resource statement.

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 names one alternative, get_narrative, for inspecting a single narrative's answers. However, it does not clarify when to use this tool versus related siblings such as get_perception or get_brand_overview, so usage guidance is present but incomplete.

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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