List the user's audits (most recent first, deduplicated by URL). Returns audit_id, url, status, total_score, created_at. Default limit 24, max 100. Use the returned audit_id with get_audit for full findings. Requires an API key.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden. It discloses key behaviors: sorting (most recent first), deduplication, default and max limits, returned fields, and API key requirement. It does not mention pagination beyond the limit or error cases, but for a list tool these are the most critical details.
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 and front-loaded with the primary action, followed by key behavioral details. Every sentence adds value: what it returns, how results are ordered and deduplicated, limits, follow-up tool, and authentication requirement. No redundancy or 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?
For a simple tool with one optional parameter and no output schema, the description covers all essential aspects: return fields, ordering, deduplication, limits, authentication, and next steps. It is fully sufficient for an agent to understand invocation and expected results.
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 single parameter 'limit' is documented in the schema as an integer 1-100. The description adds the default value (24) and max (100), which is meaningful context beyond the schema's bare range. It doesn't explicitly say 'limit' controls the number of results, but that is implied by the surrounding text.
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's function: 'List the user's audits' with specific behaviors (most recent first, deduplicated by URL). It distinguishes from siblings by mentioning that full findings require get_audit, positioning this as a summary listing tool.
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?
It provides context on when to use the tool: to list audits and retrieve summary data, and explicitly directs users to get_audit for full findings. However, it does not explicitly mention alternatives like run_audit for creating new audits or run_audit_anonymous for unauthenticated runs, though the auth requirement hints at these distinctions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.
