Transparent heuristic reputation score (0-100) combining domain age, TLS validity and email-auth strictness (SPF/DMARC) plus an MX signal. Every contribution is returned in rationale (no black box). Informational only, not a security guarantee. Read-only; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain name to score |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description discloses that the tool is read-only, free, returns a heuristic score with a rationale, and is not a security guarantee. This covers key behavioral traits, though it lacks details on rate limits or error handling.
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 concise (four sentences), front-loaded with the core purpose and components, and every sentence adds value without redundancy.
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 one parameter and no output schema, the description explains the score range (0-100), components, and that rationale is included. It is mostly complete but could benefit from specifying the output format (e.g., JSON structure).
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 only parameter 'domain' has a schema description 'Domain name to score'. The tool description reinforces this but adds no additional format, validation, or examples. With 100% schema coverage, a baseline of 3 is appropriate.
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 computes a heuristic reputation score (0-100) combining domain age, TLS validity, email-auth strictness, and MX signal. It distinguishes from sibling tools like domain_intel_dns_lookup by being a composite score rather than a raw lookup.
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 mentions 'Informational only, not a security guarantee' which provides a caution, but does not explicitly state when to use this tool over alternatives like domain_intel_email_auth_check or content_authenticity_domain_reputation.
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.
Most tools are clearly distinguished by domain prefixes (e.g., bid_watch, grant_watch) and specific action verbs. However, the high number of similarly structured watch tools could still cause confusion, though descriptions clarify exact purposes.
Every tool follows a consistent `domain_subdomain_action` pattern with underscores, e.g., `agent_audit_query`, `bid_watch_search`. Even long names like `commerce_catalog_agent_readiness_score` adhere to this structure.
With 147 tools, the server is far too broad, covering weather, carbon estimates, domain intel, and more—well beyond its stated 'Japan public-data ledgers' scope. This sheer volume overwhelms agents and dilutes focus.
The server offers many read-only tools for Japanese public data (bids, grants, licenses, etc.), but lacks create/update/delete operations for those domains. Additionally, numerous unrelated tools (e.g., carbon estimates, weather) feel tacked on, leaving gaps in core coverage.