prompteye-mcp

Official

by PROMPTEYE-SP-Z-O-O

Overview Schema Source Related Servers Discussions Admin

TypeScript

Remote

Read one content brief

get_content_brief

Read-only

Retrieve a content brief by ID to view its title, H2/H3 outline, notes, FAQs, and phrase coverage; call after create_content_brief until status is ready or error.

Instructions

One content brief in full: the article's title, its H2/H3 outline with the notes and FAQ questions for each section, the fan-out phrases it covers, and the phrases that deserve an article of their own. Call this after create_content_brief until status is ready or error; everything but the prompt is empty while it is processing.

PromptEye generates content as well as measuring visibility, and the two make one loop: track the prompts and how often the assistants name the brand on them, generate an article that targets a prompt where the brand is weak, publish it, then measure whether that prompt's visibility and citations move. Generation starts from a content brief: PromptEye fans the target prompt out into the phrases people ask around it, keeps the ones that belong in this article, sets aside the ones that deserve an article of their own, and writes a title and an H2/H3 outline from them. create_content_brief orders one and get_content_brief reads it. The article itself is written from the brief in the PromptEye app, under Content (https://app.prompteye.com/content), from the brand description, the knowledge documents picked for it and the chosen writing style; saving the live URL, requesting indexing and following citations happen there too, and publishing the page is done on the user's own site. A generated article is a draft to review, and neither it nor its indexing guarantees that an assistant will cite it. Guides: https://app.prompteye.com/help/content/ and https://app.prompteye.com/help/content/article-workflow/.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`briefId`	Yes	Id of the brief, as create_content_brief reports it.

Output Schema

TableJSON Schema

Name	Required	Description
`id`	Yes
`error`	Yes	Why generation failed. null unless status is error.
`title`	Yes	Generated article title. null until status is ready.
`prompt`	Yes
`status`	Yes	processing until generated, then ready (title and outline filled in) or error.
`outline`	Yes	The H2/H3 structure of the article. null until ready.
`readyAt`	Yes	When it finished, ISO 8601 in UTC. null = not finished yet.
`projectId`	Yes
`trackerId`	Yes	The tracked prompt the brief is linked to. null = requested standalone.
`fanoutError`	Yes	Set when the fan-out failed but the brief completed with the phrases it had. null otherwise.
`requestedAt`	Yes	When the brief was requested, ISO 8601 in UTC.
`fanoutSource`	Yes	Which fan-out engine produced the phrases. null until ready.
`originalTitle`	Yes	Title of the existing article being optimized. null = no existing article, or not ready yet.
`fanoutVariants`	Yes	Every phrase the fan-out found. null until ready.
`separateArticles`	Yes	Phrases that deserve an article of their own. null until ready.
`phrasesForArticle`	Yes	Phrases that belong in this article and built the outline. null until ready.
`titleChangeAnnotation`	Yes	Why the title changed. null = kept, no existing article, or not ready yet.
`sourceTextMatchPercentage`	Yes	How much of the phrase coverage the existing article already had, in whole percent 0-100. null = no existing article, or not ready yet.

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.0.22Oct 2, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, but the description adds real behavioral context beyond them: the brief has a status lifecycle (processing/ready/error) and returns near-empty data mid-processing, and it discloses that this tool does not write or publish the article. It stops short of richer operational detail (pagination, rate limits, size of payload).

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 return contents are correctly front-loaded, but the definition is long: the middle paragraph about PromptEye's measure/generate loop and the app-side writing workflow is largely product background that an agent does not need to invoke a read. Core instructions are buried in a wall of prose.

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 and safety annotations already present, the definition still covers everything an agent needs: what is returned, the polling/status semantics, and how it relates to create_content_brief. Nothing required to call it correctly is missing.

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%, and the single briefId parameter is already documented as coming from create_content_brief. The description adds no syntax or format detail beyond the schema, so the baseline 3 for high coverage applies.

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?

The first sentence names a specific verb (read) and resource (one content brief) and enumerates exactly what the payload contains: title, H2/H3 outline with notes and FAQ questions, fan-out phrases, and standalone-article phrases. It is clearly distinguishable from the sibling create_content_brief, which it explicitly contrasts ('orders one' vs 'reads it').

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?

It states precisely when to call it: 'Call this after create_content_brief until `status` is `ready` or `error`', and warns that everything but the prompt is empty while the brief is `processing`. This gives both the trigger condition and the polling loop, 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.

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