Discover relevant keywords for your brand using AI. Provide a seed topic and project ID to get keyword clusters, search volume estimates, and difficulty scores.
AI keyword discovery: clusters, volume estimates, difficulty scores.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | No | Brand UUID | |
| seed_topic | No | Focus topic |
Changes observed during successful MCP inspections.
v1.3.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions output types but does not state whether this is a read-only operation, any permissions required, rate limits, or side effects. For a tool performing 'discovery', this is incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words, effectively front-loading the tool's core purpose. However, it is borderline terse, offering minimal elaboration that could helpfully fill gaps.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's relative simplicity (2 params, no output schema), the description provides basic output information but lacks context about return format, limitations, or how to interpret the results. It is adequate but leaves room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond the schema's parameter definitions (project_id as 'Brand UUID' and seed_topic as 'Focus topic'), providing no additional context or usage details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs AI keyword discovery and lists specific outputs (clusters, volume estimates, difficulty scores). This distinguishes it from sibling tools like maasy_get_seo_status or maasy_generate_content, though it lacks a strong action verb+resource structure.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor are any prerequisites mentioned. The description only states what the tool does, leaving the agent to infer usage context from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.