get_ruleFetch one audit rule by id (e.g. "meta/title-length"), including what it checks, how to fix it (recommendation), its severity and score weight, a docs link, and whether it is a cloud (credit-billed) rule. Rule ids appear in report topIssues and issue rule_id fields.
| Name | Required | Description | Default |
|---|---|---|---|
| rule_id | Yes | Rule id like "crawl/canonical-chain" (category/slug). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and destructiveHint=false. Description adds specific return fields and context (e.g., cloud flag, docs link), enhancing transparency beyond annotations without contradiction.
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 concise sentences front-loaded with purpose; every sentence adds essential detail 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 low complexity (1 param, no output schema, annotations present), description fully covers what the tool returns and why it's useful, including source of rule ids.
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 covers the single parameter with description, but description adds examples (e.g., 'meta/title-length') and context on where rule ids appear, providing additional value beyond schema.
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 fetches one audit rule by id, listing specific fields like checks, recommendation, severity, score weight, docs link, and cloud flag. It distinguishes from sibling list_rules by specifying single rule retrieval.
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?
Explicitly mentions when to use (fetch a specific rule by id) and where rule ids come from (report topIssues, issue rule_id). Implies not for listing all rules, but does not explicitly state alternatives.
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 maps to a distinct resource-action pair: websites, audits, issues, rules, credits, notifications, and account info are cleanly separated. Even the close pairs (delete_website vs delete_websites, get_rule vs list_rules) are clear singular/bulk or fetch-all vs fetch-one distinctions.
All tool names follow a consistent snake_case verb_noun pattern: add_, delete_, get_, list_, run_, comment_, send_, create_. The only outlier, whoami, is a conventional standalone command and does not break the overall predictability.
At 20 tools, the surface is slightly heavy, but the count is justified by the wide domain coverage: audit lifecycle, issue tracking, rule catalog, billing/credits, notifications, and account management. Each tool appears to earn its place, and none feel redundant.
The core workflow is well covered: run an audit, poll it, fetch a report, compare audits, list and comment on issues, browse rules, and manage websites. Minor gaps exist—no cancel-audit tool, no update_website, and issues cannot be status-changed—but agents can work around these using the existing tools.