Transparent heuristic IP risk score (0-100) combining classification, datacenter and reverse-DNS signals; every contribution is returned in the rationale. Informational only. Read-only; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IPv4 or IPv6 address |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states 'Read-only,' 'Informational only,' and 'price 0.0 (free),' disclosing safety and cost. It also mentions transparency of the heuristic and that every contribution is returned in the rationale, which gives insight into the output structure. This goes beyond minimal disclosure, though it doesn't cover error handling or invalid inputs.
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 highly concise, delivered in two short sentences. It front-loads the primary purpose (risk score) and then adds essential context (informational, read-only, free) without any filler or 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?
For a tool with a single parameter and no output schema, the description is quite complete. It specifies what the tool does, what it returns (score plus rationale), its safety profile (read-only, informational), and its cost. Given the simplicity, there are no major gaps that would impede an agent from selecting and using it correctly.
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 'ip' is fully described in the schema as 'IPv4 or IPv6 address,' achieving 100% schema description coverage. The description does not add additional parameter-specific semantics beyond referencing the signals used, but the baseline of 3 is appropriate because the schema already documents the parameter adequately.
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 computes a heuristic IP risk score (0-100) by combining classification, datacenter, and reverse-DNS signals, with each contribution returned in the rationale. This specific verb+resource+scope distinguishes it from sibling tools like ip_reputation_classify_ip and ip_reputation_reverse_dns, which each target a single signal.
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 this is a composite score by mentioning it combines classification, datacenter, and reverse-DNS signals, suggesting use when a single aggregate risk score is needed rather than individual lookups. However, it does not explicitly state when to use this versus alternatives or provide any exclusions, so guidance is merely implied rather than explicit.
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.