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PROMPTEYE-SP-Z-O-O

prompteye-mcp

Official

List the exact pages assistants cite

list_source_pages
Read-only

Rank the individual pages AI assistants cite for a brand, showing each URL's citation share. Call when domain rankings don't show which page carries or quotes the brand.

Instructions

The individual pages behind list_sources — each row is one URL, not a domain, so a host cited on several different pages shows up once per page instead of folded into one domain total. Call this when the domain ranking does not say enough: which page of a review site carries the brand, or which own page the assistants actually quote.

A citation is not visibility: an answer can cite the brand's own domain without naming the brand, and name the brand while citing nobody. Read this beside list_prompts and list_competitors, not instead of them.

The ranking is built by adding up the period, so it answers with the limit most cited pages rather than a list to walk to the end of; share is each page's slice of the occurrences across the pages reported. model narrows it to one assistant.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many pages to return, at most 200.
modelNoReport on this assistant alone instead of all of them.
endDateNoLast day to report on, inclusive. Defaults to today, and must be within 366 days of startDate.
startDateNoFirst day to report on, inclusive. Defaults to 30 days before today.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
nextCursorYesPass as cursor to read the next page. null = this was the last page.

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 declare read-only and open-world, so the description carries the interpretive load and does: it explains the aggregation method ('adding up the period'), that `limit` is a top-N cutoff rather than a pagination cursor, and how `share` is computed. It also warns that citation is not visibility, a genuine behavioral caveat the agent could not infer from structure.

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?

Three paragraphs, front-loaded with the defining distinction, then usage, then semantics. Dense but nearly every sentence carries non-redundant information; the citation-vs-visibility aside is valuable but slightly discursive.

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?

An output schema exists so return values need not be documented, yet the description still explains `share` and the ranking basis, closing the only interpretive gap. For a 4-param read tool with full schema coverage, nothing an agent needs is missing.

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?

Schema description coverage is 100%, so baseline is 3; the description exceeds it by clarifying that `limit` returns the most cited pages rather than a walkable list, and that `model` narrows to a single assistant. Date parameters are left to the schema, which is acceptable given full coverage.

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 resource (individual cited pages) and immediately fixes the granularity: 'each row is one URL, not a domain,' which distinguishes it from its nearest sibling list_sources. An agent can tell exactly what this returns versus the domain-level ranking.

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 trigger ('Call this when the domain ranking does not say enough') plus concrete motivating questions, and routes the agent to companions ('Read this beside list_prompts and list_competitors, not instead of them'). When-to-use and when-not-to-replace are both covered.

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