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

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. create_article then writes the article from a ready brief, from the brand description, the knowledge documents picked for it and the chosen writing style; get_article reads its text and list_articles lists the project's articles, also those added in the app under Content (https://app.prompteye.com/content). Publishing the page is done on the user's own site; publish_article then records the URL it went live at, and requesting indexing and following citations happen in the app. 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

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

Output 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

A3.9/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the bar is lower, yet the description adds real value: the processing-vs-ready state semantics and the fact that fields are empty during processing. It does not discuss authorization or whether briefs expire, but the polling behavior is well disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first two sentences are well front-loaded and earn their place, but the remainder is product narrative about PromptEye's measure-generate-measure loop, article creation, publishing on the user's own site, and indexing in the app — none of which an agent needs to read one brief. Multiple links and sibling walkthroughs make it far longer than the task requires.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present and rich annotations, the description need not explain return values, and it still covers the state machine an agent must handle. It is complete for correct invocation, though the completeness comes wrapped in a large amount of unrelated workflow copy.

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% and the single parameter `briefId` already carries 'Id of the brief, as create_content_brief reports it.' The description adds no format or sourcing detail beyond referencing create_content_brief, so baseline 3 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?

Opens with a specific verb+resource ('One content brief in full') and enumerates exactly what the record contains: title, H2/H3 outline with notes and FAQ questions, fan-out phrases, and phrases deserving their own article. This clearly separates it from create_content_brief (which orders one) and get_article (which reads finished article text).

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?

Explicitly says to call it after create_content_brief and to poll until `status` is `ready` or `error`, and warns that everything but the prompt is empty while `processing`. That is strong lifecycle guidance, though it never states when not to use it (e.g., to list briefs or to read a published article).

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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