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PROMPTEYE-SP-Z-O-O

prompteye-mcp

Official

Read one prompt

get_prompt
Read-only

Retrieve a prompt's visibility per AI assistant to spot which ones carry the brand and which drop it, with an optional date range.

Instructions

One prompt of the active project, with its visibility broken down per assistant. Call this to see which assistant is carrying a prompt and which is dropping the brand from it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endDateNoLast day to report on, inclusive. Defaults to today, and must be within 366 days of startDate.
promptIdYesId of the prompt, as list_prompts reports it.
startDateNoFirst day to report on, inclusive. Defaults to 30 days before today.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.5

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already mark this as read-only, so the description needs to add value beyond safety. It does so by explaining the output shape ('visibility broken down per assistant') and the analytical purpose (identifying which assistant drops the brand). This is useful behavioral context with no contradiction to readOnlyHint or openWorldHint.

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?

Two sentences with zero fluff. The first sentence states what the tool returns, and the second gives a concrete reason to call it. Information is front-loaded and every sentence earns its place.

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?

Given the tool's low complexity, full parameter schema, and read-only annotations, the description is complete. It explains the return value concept (per-assistant visibility) beyond just naming the resource, which covers the absence of an output schema. An agent has enough to select and invoke it correctly.

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 description coverage is 100%, so the schema already documents promptId, startDate, and endDate. The description adds no additional parameter-level meaning; it describes the tool's purpose rather than clarifying parameter usage. Baseline 3 is appropriate.

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 uses a specific verb ('Read' in title, 'Call this to see' in body) with a clear resource: one prompt of the active project. It distinguishes itself from list_prompts by focusing on a single prompt, and from visibility summaries by specifying the per-assistant breakdown and the brand-carrying/dropping insight.

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 a clear context for use: 'Call this to see which assistant is carrying a prompt and which is dropping the brand from it.' This tells an agent when this tool is appropriate, though it doesn't explicitly name alternatives or state when not to use it, so it falls short of a full when/when-not spec.

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