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competlab-mcp-server

get_ai_visibility_history

Retrieve paginated history of AI Visibility checks to monitor how ChatGPT, Claude, and Gemini ranked your brand across previous monitoring cycles.

Instructions

Get paginated history of AI Visibility checks with completion timestamps. Note: uses checkId (not runId) — AI Visibility has a different data model where each check is one 3-prompt x 3-LLM query cycle. Use this to browse past checks; retrieve full detail with get_ai_visibility_check_detail, or use get_ai_visibility_trend for aggregate time-series. Read-only. Returns paginated JSON array with pagination.hasMore flag.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID (from list_projects)
pageNoPage number (1-indexed, default: 1)
limitNoItems per page (default: 20, max: 100)
Behavior4/5

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

With no annotations provided, description carries full disclosure burden. It states 'Read-only' (safety), describes return structure ('paginated JSON array with pagination.hasMore flag'), and explains the data model ('each check is one 3-prompt x 3-LLM query cycle'). Missing only rate limits or error semantics.

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?

Every sentence earns its place: purpose front-loaded, data model note follows, usage guidance with alternatives next, read-only declaration, then output format. Zero redundancy despite covering distinct operational aspects in 3-4 efficient sentences.

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?

Excellent completeness for a list tool with no output schema. Compensates by describing the pagination structure (hasMore flag) and read-only nature. Clarifies domain terminology (checkId vs runId) that would confuse users familiar with other tools using runId.

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% (projectId, page, limit all fully documented). Description does not add parameter-specific guidance, but baseline 3 is appropriate given the schema's completeness. The mention of 'checkId' refers to output data, not input parameters.

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?

Description opens with specific verb+resource ('Get paginated history of AI Visibility checks') and explicitly distinguishes from siblings get_ai_visibility_check_detail ('retrieve full detail with...') and get_ai_visibility_trend ('for aggregate time-series'), clarifying the unique scope of this list/browsing tool.

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

Usage Guidelines5/5

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

Provides explicit when-to-use ('Use this to browse past checks') and clear alternative selection criteria: use get_ai_visibility_check_detail for full detail, get_ai_visibility_trend for aggregates. Also clarifies domain-specific ID confusion (checkId vs runId) to prevent misuse.

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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