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AKzar1el

GEO MCP by DigestSEO

Set active prompts

set_prompts
DestructiveIdempotent

Replace a brand's active prompts with an exact set for future scans, preserving history. Specify brand ID and 1-50 prompts to update AI visibility tracking.

Instructions

Replace a brand's active prompts with an exact supplied set; history is preserved. Example: brand_id='acme', prompts=['What is the best X for Y?'].

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptsYesExact 1-50 prompt set for future scans.
brand_idYesTracked brand ID to update.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
changedYes
promptsYes
brand_idYes
next_stepsYes
prompts_insertedYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.3.23
    • changedInput schema / properties / brand_id / description
      Previous value: -"Stable identifier of the tracked brand to update."New value: +"Tracked brand ID to update."
    • changedInput schema / properties / prompts / description
      Previous value: -"Exact active prompt set to use for future scans (1-50 questions)."New value: +"Exact 1-50 prompt set for future scans."
  2. Addedv0.3.17

TDQS

A4.2/5.0
Behavior4/5

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

Annotations indicate destructiveHint=true and idempotentHint=true. The description adds that history is preserved, which is important context not captured in annotations: although destructive, it doesn't destroy the history. This enriches the behavioral understanding.

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?

The description is two sentences: the first is the core function, the second provides a concrete example. It is front-loaded and has no filler. Every word contributes to clarity.

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?

Given the simple two-parameter tool with full schema coverage and an output schema, the description is sufficient. It covers the replacement behavior, preservation of history, and an example. The only minor gap is not specifying the return value, but the output schema likely provides that.

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 both parameters are well-documented in the schema. The description adds the example, which clarifies the exact format expected, and clarifies that 'prompts' is the exact set to be set. It does not add new meaning beyond the schema but reinforces the purpose.

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 description clearly states it replaces a brand's active prompts with an exact supplied set, distinguishing it from sibling list_prompts and generate_prompts. It uses a specific verb 'Replace' and indicates the resource (brand's active prompts) and the nature of the operation (overwrite with exact set).

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?

The description gives a concrete example showing the expected parameters (brand_id and prompts) and implies the tool is for setting prompts, contrasting with siblings like generate_prompts. It does not explicitly state when not to use it, but the example and wording provide clear usage context.

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