Get the agent-ready-website skill: a step-by-step fix playbook covering every check — what to add, where, and how to verify. Refetched each run so it matches the current check set.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly discloses that the data is refetched each run (live, not cached) and describes the content as a step-by-step playbook with verification steps. This gives the agent useful behavioral context about freshness and structure. No contradictions with missing annotations.
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 two sentences, each pulling weight. The first sentence defines the resource and its nature, the second adds a key behavioral note (freshness). No fluff or redundancy. Excellent conciseness.
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 there are no parameters, no annotations, no output schema, and the tool is simple (parameterless retrieval), the description covers the essential: what it returns, its liveness, and its structure (playbook). It could possibly mention the format or size of the returned playbook, but for a tool of this simplicity, it is complete 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?
The input schema has zero parameters and 100% schema description coverage, so the baseline is high. The description adds value by explaining what the tool returns (the fix playbook), which goes beyond the empty schema. For a parameterless tool, this is adequate.
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 it retrieves a specific 'agent-ready-website skill' which is a step-by-step fix playbook. The verb 'Get' is clear, and the resource is named. It distinguishes itself by noting it is refetched each run, which hints at liveness. However, it could be more explicit about how it differs from sibling tools like 'get_checks' or 'get_score'.
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 implies the tool is used to retrieve a fix playbook for checks, which gives some context for when to use it. However, it does not explicitly state when to use this tool over alternatives like 'get_checks' or 'scan_domain', and provides no 'when not to use' guidance. The context is implied but could be clearer.
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.
Tools are generally well-distinguished, but discover_products and search_capabilities could be confused since both search across domains. The difference in query type (task intent vs. capability) is somewhat subtle. Overall, most tools have clear, separate purposes.
All tool names use a consistent verb_noun pattern (e.g., discover_products, get_checks, scan_domain). The naming is predictable and matches the server's domain of evaluating agent-ready properties.
With 11 tools, the server covers scanning, scoring, feedback, and search without being overly broad. Each tool has a distinct role, and the count is appropriate for the focused purpose of assessing agent readiness.
The tool set covers the full lifecycle: discover/scan domains, get scores and checks, apply skills, verify with challenges, submit feedback and disputes. There are no obvious missing operations for the stated domain.