Return a signed download URL for the branded PDF report for a given audit id. If no PDF has been rendered yet, queues a render and returns status: queued — poll the same tool again, or fetch the URL directly once ready. Requires an API key.
| Name | Required | Description | Default |
|---|---|---|---|
| audit_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must convey behaviors itself. It discloses the asynchronous queuing behavior, the 'queued' status response, and the need to poll or fetch later. Also requires an API key. This is sufficiently transparent for a read-only URL generation tool.
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 concise, using two sentences to present the core function, conditional behavior, and auth requirement. Every sentence carries meaningful information without fluff.
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 simplicity (one parameter, no output schema), the description covers the main behavioral nuances: URL generation, queuing fallback, and polling guidance. It also mentions the API key requirement. This is sufficiently complete for an agent to invoke the tool correctly, though it does not explain the difference from sibling tools beyond the tool name.
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?
The schema includes only audit_id (string, minLength 1) with no parameter description (0% schema coverage). The description's phrase 'for a given audit id' adds context that audit_id serves as the identifier for the audit report. This is minimal but adequate for a single obvious parameter.
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 identifies the tool's function: returning a signed download URL for a branded PDF report for a given audit ID. It uses a specific verb ('Return') and names the resource ('download URL for the branded PDF report'), distinguishing it from sibling tools like get_audit and list_audits.
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 context (when you need the PDF report) relative to other audit-related tools, and notes an API key requirement. However, it does not explicitly state when not to use this tool or name alternative tools for other scenarios.
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 resource or action: get_audit retrieves JSON findings, get_audit_pdf fetches a PDF, list_audits enumerates prior audits, run_audit queues an authenticated audit, run_audit_anonymous runs a sync anonymous audit, and get_organic_traffic provides Google-linked analytics. The two audit-running tools are clearly differentiated by auth and synchronicity, and the descriptions explicitly contrast them.
All tool names follow a consistent verb_noun snake_case pattern: get_*, list_*, run_*. The two run tools share the same verb with a descriptive suffix (_anonymous), maintaining a predictable and readable convention.
Six tools is well within the ideal 3-15 range for an SEO audit MCP. Each tool serves a distinct phase of the audit workflow (trigger, retrieve, list, report, analytics), earning its place without redundancy.
The tool set covers the full audit lifecycle: initiating audits (both anonymous and authenticated), retrieving results, listing historical audits, generating PDF reports, and accessing traffic analytics. No obvious gaps exist; the domain is fully addressed for a read-centric audit API.
