Fetch a previously-run audit by id. Returns module scores (0-100), total score, all findings with severity, recommendation text, and links to the HTML report. Use this to poll a queued run_audit until status: complete. Requires an API key.
| Name | Required | Description | Default |
|---|---|---|---|
| audit_id | Yes |
Does 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 the API key requirement, describes the return payload in detail, and clarifies the polling usage pattern. It does not cover error behavior or rate limits, but for a simple read-only fetch it provides strong context.
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?
Three sentences, all information-dense with no filler. The purpose is front-loaded, then return data, then usage guidance. Every sentence earns its place.
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?
For a one-parameter tool with no output schema, the description covers the core action, return values, authentication, and the intended polling scenario. It does not mention error behavior or edge cases, but these are not critical for this simple fetch operation.
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 0% and the description only says 'by id', offering no additional meaning beyond the schema's audit_id field. It does not specify the format, source, or how to obtain the audit ID, so the description fails to compensate for the lack of parameter 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 states a specific verb ('Fetch') and resource ('previously-run audit by id'), clearly distinguishing it from siblings like get_audit_pdf and list_audits. It also enumerates the exact return contents, leaving no ambiguity about the tool's function.
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 explicitly says to use this tool to poll a queued run_audit until status: complete, and notes it is for previously-run audits. It references the sibling run_audit but does not explicitly exclude alternatives like get_audit_pdf or list_audits, which slightly weakens the guidance.
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.
