Scan a website for SEO, performance, accessibility, and AI search issues. Returns structured issues with LLM-ready fix instructions.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The full URL to scan, e.g. https://example.com |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions returning structured issues with LLM-ready fix instructions but omits critical details like sync/async nature, rate limits, timeouts, or any side effects (e.g., does it modify data?).
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 sentences that are efficient and front-loaded: the first gives the core purpose, the second describes the output. No wasted words.
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 tool has no output schema and one parameter, but the description lacks details on return format, pagination (sibling 'next_issue' hints at this), limits, or performance expectations. For a scanning tool, this is incomplete for an agent to use effectively.
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 coverage is 100% for the single parameter 'url', and the description adds no new meaning beyond the schema's description. Baseline 3 is appropriate as it does not detract but also does not enhance.
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 scans websites for SEO, performance, accessibility, and AI search issues, providing a specific verb and resource. It distinguishes itself from siblings like 'get_scan' (retrieving results) and 'next_issue' (navigation) by being the initiation action.
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?
No explicit guidance on when to use this tool versus alternatives. The context of sibling names implies it is for starting a scan, while 'get_scan' retrieves results, but the description does not state this distinction or provide usage conditions.
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 unique purpose: triggering scans, retrieving results by ID, obtaining full site intelligence, or getting a single actionable issue. No overlap or ambiguity.
Three tools follow verb_noun pattern (get_scan, get_site_intelligence, scan_website), but 'next_issue' deviates slightly as it omits a verb. Still, the naming is clear and consistent in style.
With 4 tools, the server is well-scoped for an SEO analysis workflow. Each tool is essential, and the count avoids unnecessary complexity.
Covers the core workflow: scan, retrieve results, get intelligence, and get prioritized tasks. Minor gap: no way to list all scans or bulk view issues, but 'next_issue' fills the action-oriented need.
