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PROMPTEYE-SP-Z-O-O

prompteye-mcp

Official

Check which integrations the project has

get_integrations_status
Read-only

Verify that Search Console, Google Analytics, bot tracker, and sitemap are connected to the active project. Call before reporting zero traffic to distinguish missing integrations from empty data.

Instructions

Whether Search Console, Google Analytics, the bot tracker and the sitemap are connected to the active project, in one call. Call it before reporting a zero or an empty list from get_search_performance, get_ai_traffic, list_bot_visits, count_bot_visits or list_crawls: a project with nothing connected answers those with zeros and empty lists, which reads exactly like a site nobody visits.

connected: false means the integration is missing, never that the site had no traffic. reason: sync_failing means it is connected but its last sync failed, so its figures are stale; get_google_status and get_sitemap say when and why. Integrations are connected in the PromptEye app.

PromptEye has no CMS integration. The WordPress and Laravel collectors are ways of installing the bot tracker and are reported under botLogs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
botLogsYes
sitemapYes
analyticsYes
searchConsoleYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.22

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only cover readOnlyHint/openWorldHint; the description adds real behavioral semantics: what `connected: false` means versus `reason: sync_failing`, that the figures in downstream tools would be stale, and that Google/sitemap siblings explain the failure. It also discloses scope limits (no CMS integration; WordPress/Laravel are collector install paths reported under `botLogs`), which preempts a plausible misreading.

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?

Front-loads the one-sentence purpose, then the routing rule, then field semantics, then edge-case exclusions — a sensible ordering. It runs a bit long, and the final WordPress/Laravel sentence is the softest, but each sentence carries a distinct disambiguating fact and none is redundant.

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 an output schema present the description needn't restate return structure, yet it still explains the semantics of the two output signals an agent is most likely to misread. Combined with the sibling routing and the explicit scope exclusions, an agent has everything needed to call this tool correctly and interpret it.

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?

The tool takes zero parameters, so the baseline is 4; there is no parameter syntax for the description to add. The description instead clarifies the implicit 'active project' scope, which is the only input-like thing that matters here.

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 — reports whether Search Console, Google Analytics, the bot tracker and the sitemap are connected to the active project — and explicitly distinguishes itself from the traffic/reporting siblings by describing itself as a single connectivity check. An agent can tell at a glance this is a precondition/diagnostic tool, not a data 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?

Gives an explicit when-to-call rule ('call it before reporting a zero or an empty list from get_search_performance, get_ai_traffic, list_bot_visits, count_bot_visits or list_crawls') and explains the failure mode it prevents. It names four concrete alternative tools and the exact condition that selects this one, leaving nothing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.