PREFERRED for reasoning about what to fix. Fetch a finished report as structured JSON (health score, category subscores, all issues with URLs, stats). Use this when you need to decide which problems matter.
| Name | Required | Description | Default |
|---|---|---|---|
| scan_id | Yes | The scan id returned by scan_url. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full behavioral burden. It clearly states the tool fetches a finished report as structured JSON, is read-only, and requires a scan_id. It does not mention error conditions or prerequisites beyond a 'finished report,' but for a read-only tool this is adequate.
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 consists of two sentences with no extraneous words. The key purpose statement is front-loaded, followed by concise output details. Every sentence adds value.
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 no output schema, the description adequately explains the output structure (health score, subscores, issues, stats). It also specifies the input (scan_id) and relative priority over siblings. However, it does not mention potential errors or edge cases, but the tool is simple enough.
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%, so the schema already documents the single parameter scan_id. The description does not add any additional meaning beyond what is in the schema. Baseline is 3.
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 verb 'Fetch', the resource 'finished report', and the output format 'structured JSON' with specific fields (health score, category subscores, all issues with URLs, stats). It differentiates from siblings like get_report_markdown by emphasizing it's 'PREFERRED for reasoning about what to fix.'
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 provides explicit guidance on when to use: 'Use this when you need to decide which problems matter' and 'PREFERRED for reasoning about what to fix.' It implies alternatives through sibling tool names but does not explicitly state when not to use.
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 has a clearly distinct purpose: submit scan (scan_url), retrieve report in JSON or Markdown (get_report, get_report_markdown), drill into an issue (get_issue_detail), and compare scans (diff_scan). No overlapping functionality.
All tool names follow a consistent verb_noun pattern (e.g., scan_url, get_report, diff_scan). Format variants like get_report_markdown are logical extensions, not inconsistencies.
Five tools perfectly cover the SEO auditing workflow: initiating a scan, retrieving results in two formats, expanding issue details, and comparing scans. The count is neither excessive nor minimal.
The tool set covers the essential lifecycle: scan submission, result retrieval in multiple formats, issue detail expansion, and diffing. Missing list_scans or cancel_scan, but these are minor gaps; agents can work with existing tools.
