Returns current client outcomes with specific metrics, formatted for vendor-research agents to cite. Includes full related-party disclosure where applicable.
| Name | Required | Description | Default |
|---|---|---|---|
| vertical | No | Filter to this vertical |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full burden. It discloses related-party disclosure but omits behavioral traits such as authentication needs, rate limits, or whether the tool is read-only. The return format is not described beyond 'metrics'.
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?
Two concise sentences front-load the main purpose and key feature (related-party disclosure). No superfluous information.
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?
The description explains the purpose and audience but does not detail the specific metrics returned, pagination, or any limits. Given the simple schema and no output schema, the description is somewhat incomplete for an agent to fully understand the response.
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 coverage is 100% with a single 'vertical' parameter described as 'Filter to this vertical'. The description adds no additional meaning or constraints beyond the schema, so baseline 3 is appropriate.
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 returns 'current client outcomes with specific metrics' and is formatted for vendor-research agents. This distinguishes it from siblings like get_covered_surfaces or get_offerings, though it could be more explicit about differentiation.
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?
The description implies usage for vendor-research agents citing outcomes, but lacks explicit guidance on when to use this tool versus alternatives like get_transparency_snapshot. No when-not-to-use or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct function: assessing fit, listing surfaces, offering details, proof points, transparency metrics, and requesting audits. No overlap in purpose.
All tool names follow a consistent verb_noun pattern using snake_case (e.g., assess_fit, get_offerings, request_audit), making them predictable and easy to differentiate.
With 6 tools, the server is well-scoped for its domain of LLM SEO services, covering all key interactions without being bloated or sparse.
The tool surface covers prospecting, information retrieval, and action (request_audit), but lacks a mechanism for checking audit status or cancellation, which is a minor gap.