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devtune_get_visibility_summary

Read-onlyIdempotent

Get AI search visibility summary metrics for a project. The default aggregates only the project’s currently active platforms and returns measurement metadata; use only measurement.reportablePlatforms for current per-platform reporting. This excludes configured onboarding platforms that have no measurements in the window. measurement.dataStatus=no_data means the platform was not measured in the window, not that visibility was zero. Inactive historical data is excluded unless explicitly requested. Organic percentage fields use 0 to 100; citationPresence and shareOfVoice are null when no response has usable citation data, shareOfVoice also when neither the primary brand nor a competitor was cited, and brandAwareness is null when no answer was measured. shareOfVoiceRange, citationPresenceRange and brandAwarenessRange hold the rate as value with a 90% range as low and high in percent, successes, the answer or citation count n and nEffective; directional true means too few to rely on. advertising reports separate forward-only ads detected, measuredResponses coverage, and primaryRate/competitorRate fractions from 0 to 1, null when unmeasured, each with a primaryRateRange/competitorRateRange 90% range in the same unit. Never combine advertising with organic Presence. platformCadences lists each platform’s cadenceDays; window figures include weekly platforms, and lastCheckedOn gives the last date a weekly platform was checked. promptScope=unbranded leaves out topics whose every prompt names the project’s own brand, as the dashboard headline does; the default all counts every topic. advertising counts every topic whatever promptScope is.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "devtune_get_visibility_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault
topicIdNoFilter by topic UUID.
platformNoFilter by AI platform (e.g. chatgpt, perplexity, gemini).
windowDaysNoRolling window in days: 30 or 90. Defaults to 30.
promptScopeNoWhich topics to count: all (default), branded (only topics whose every prompt names the project’s own brand) or unbranded (every other topic, mixed ones included). Prompts that name the brand usually get it mentioned, so unbranded matches the dashboard headline. Applies together with topicId.
includeHistoricalPlatformsNoInclude data from a requested inactive platform. Defaults to false and should only be enabled when the user explicitly asks for historical platform data.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / promptScope
      Added value: +{
      +  "description": "Which topics to count: all (default), branded (only topics whose every prompt names the project’s own brand) or unbranded (every other topic, mixed ones included). Prompts that name the brand usually get it mentioned, so unbranded matches the dashboard headline. Applies together with topicId.",
      +  "enum": [
      +    "all",
      +    "branded",
      +    "unbranded"
      +  ],
      +  "type": "string"
      +}
  2. Changed3 schema fields changed
    • addedInput schema / properties / platform / maxLength
      Added value: +100
    • addedInput schema / properties / platform / minLength
      Added value: +1
    • addedInput schema / properties / topicId / format
      Added value: +"uuid"
  3. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive behavior, and the description adds rich behavioral detail beyond them: reportablePlatforms versus configured onboarding platforms, null semantics for citation/share/awareness fields, directional flags, range structure, cadence handling, and advertising/organic separation. There is no contradiction with the annotations.

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

Conciseness3/5

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

The purpose is front-loaded, but the body is a dense wall of semicolon-separated metric rules with no grouping or bullets. Much of the content is relevant given the absence of an output schema, but scanability and structure are weak.

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

Completeness5/5

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

With no output schema, the description must carry return-value semantics, and it does so extensively: measurement metadata, reportable platforms, null conditions, ranges, advertising units, cadences, and promptScope effects. Completeness is high despite poor organization.

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?

All five parameters have full schema descriptions, so the baseline is 3. The description restates promptScope and historical-platform semantics and adds an advertising exception, but does not materially extend topicId, platform, or windowDays semantics beyond the schema.

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?

States a specific verb and resource: "Get AI search visibility summary metrics for a project." It makes clear this is aggregate summary data, but it does not name or explicitly distinguish sibling tools such as devtune_get_visibility_diff or devtune_get_visibility_response.

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?

Provides substantial operational context: default active-platform aggregation, dataStatus=no_data interpretation, historical exclusion unless explicitly requested, promptScope default behavior, and the warning never to combine advertising with organic Presence. However, it never says when to choose this tool over sibling visibility tools, so full routing guidance is missing.

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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