Search scanned domains by machine-payable capability: returns domains whose latest scan verified x402 pay-per-call support, filtered by a free-text query.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (default 10) | |
| query | Yes | Free-text filter over domain, name, and capability details |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions that results are based on the latest scan and that filtering is by free-text query. Since no annotations are provided, the description carries the full burden. It doesn't disclose whether results are real-time or cached, whether query is case-sensitive, or what happens if no matches are found. The behavioral disclosure is adequate but not thorough.
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 a single, front-loaded sentence that efficiently conveys the core purpose and filtering mechanism. Every part adds value: 'scanned domains', 'machine-payable capability', 'latest scan verified x402 pay-per-call support', and 'free-text query'. No superfluous 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 2 parameters (both simple), no output schema, and no annotations, so the description must cover purpose, behavior, and parameter semantics. It does this well: purpose is clear, filtering explained, and parameter semantics partially covered. It doesn't describe the return format or edge cases, but for a search tool this is acceptable given the context signals.
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 description coverage is 100%, so the parameters 'query' and 'limit' are already documented in the schema. The description adds the detail that query is a free-text filter over 'domain, name, and capability details', which provides some semantic enrichment. However, it doesn't elaborate on the format of query or the default value for limit beyond what the schema says.
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 specifies the verb 'search', the resource 'scanned domains', and the filtering criterion 'machine-payable capability' with x402 pay-per-call support. It distinguishes itself from sibling tools like scan_domain (which performs scans) and discover_products (which likely lists products) by focusing on capability-based search of existing scan results.
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 implicitly states when to use the tool: when you need to find domains that have confirmed pay-per-call support. However, it does not explicitly say when NOT to use it or mention alternative tools for other use cases (e.g., use scan_domain first if a domain hasn't been scanned). It provides minimal usage context.
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.