Mencoro

Discover AI prompts

discover_prompts

Start a background job that proposes the questions people ask AI assistants about a topic in one country - the prompts worth tracking on AI engines. excludeQueries leaves out ones already tracked. Poll get_job for the result, review it with the user, then track the chosen ones with create_tracked_queries. Requires an active subscription.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "organizationId": "<organizationId>",
      "projectId": "<projectId>",
      "input": "<input>",
      "country": "<country>"
    },
    "name": "discover_prompts"
  }
}

Input Schema

Name	Required	Description
`input`	Yes
`country`	Yes
`language`	No
`projectId`	Yes
`requestId`	No	Optional idempotency key, 8-255 printable characters. Reuse it only to retry this same call.
`excludeQueries`	No
`organizationId`	Yes

Output Schema

Name	Required	Description
`jobId`	Yes	Pass it to get_job. May name a job started by an earlier, equivalent call.
`nextStep`	Yes
`deduplicated`	Yes	Whether this call joined a job that was already running instead of starting one

Schema Changelog

Changes observed during successful MCP inspections.

AddedSep 28, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and openWorldHint=true, so the write/open-world profile is covered. The description adds that the work is asynchronous (background job) and requires an active subscription, which are genuinely useful behavioral facts. It stops short of detailing job timing or failure behavior, so a 4 is appropriate.

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 purpose, then the workflow and the subscription requirement in economical sentences. Slightly dense in the middle sentence but every clause carries actionable meaning.

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

Completeness3/5

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 explained, and the async workflow is covered. However, for a seven-parameter tool with very low schema coverage, the description omits meaning for most inputs, leaving the definition only partially complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 14%, so the description must compensate, yet it only explains excludeQueries. The other six parameters (input, country, language, projectId, organizationId, requestId) get no semantic explanation in either field, leaving most of the interface undocumented.

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: 'Start a background job that proposes the questions people ask AI assistants about a topic in one country.' It clearly distinguishes itself from the sibling discover_brands and discover_keywords by naming the artifact it produces (prompts/questions).

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?

Provides an explicit workflow and alternative routing: poll get_job for results, review with the user, then use create_tracked_queries, and it explains that excludeQueries drops already-tracked ones. It also states the prerequisite (active subscription). Nothing is left 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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