Ownership record for an IP address or block via RDAP: the network name, owning organization, ASN, CIDR range, and country. Pairs with ip_reputation and entity lookups. Keyless.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IPv4 or IPv6 address, e.g. '8.8.8.8'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds useful behavioral context by mentioning the RDAP source and 'Keyless' authentication, providing value beyond the structured annotations without contradicting them.
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 three sentences, approximately 25 words, with the core purpose and return fields front-loaded followed by complementary tool references and auth note. No sentence is wasted, and the structure is easy to scan.
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 its simplicity (one parameter, no output schema), the description is complete: it states what is returned, the data source, the auth requirement, and how it fits with adjacent lookups. The absence of an output schema is compensated by the explicit list of returned fields.
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 schema already documents the single 'ip' parameter with 100% coverage, including format guidance ('IPv4 or IPv6 address'). The description does not add new parameter-level semantics; it lists return fields but these are outputs, not parameter meaning, so the 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 states a clear purpose: returning an ownership record for an IP address or block via RDAP, and enumerates the specific fields returned (network name, owning organization, ASN, CIDR range, country). The IP-specific naming and content distinguish it from sibling tools like rdap_domain without needing to open schemas.
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 provides clear contextual usage signals: it pairs with ip_reputation and entity lookups, and explicitly notes it is keyless, which informs an agent that no authentication is required. It does not explicitly state when not to use it or name alternatives, but the IP focus and sibling names make the boundary evident enough.
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.
Many tools overlap heavily across domains: caselaw_search vs court_case_search vs court_opinion_search, caselaw_citation_lookup vs court_citation_resolver, and a cluster of company due-diligence tools (company_trust_check, counterparty_risk_score, entity_dossier, issuer_diligence_dossier, kyb_aml_evidence_case_file) that all screen a company for sanctions/risk/standing. With 290 tools, an agent will frequently face multiple equally plausible choices for the same user intent.
The vast majority of tools follow a clean domain-prefix + snake_case pattern (census_, eia_, fmcsa_, npi_, cfpb_, etc.), but there are notable exceptions: entity_resolve and resolve_entity are reversed duplicates, reg_search (Federal Register) sits next to reg_cfr_search (CFR) with confusingly similar names, and carrier_monitor_recheck deviates from the carrier_vetting_* family.
290 tools is an extreme count under any rubric, far exceeding even the 50+ threshold for the lowest score. While the group-filtering mechanism and meta-tools like list_tool_groups and search_available_datasets mitigate the practical burden, the raw surface is still massively oversized for an agent to select from accurately and efficiently.
For a read-only data-aggregation server, coverage is remarkably comprehensive across 59 domains, and generic fallbacks like cdc_dataset_query, eia_series_lookup, fred_observations, and bls_series prevent most dead ends. Minor gaps exist (a single GitHub tool, demo-only property_lookup coverage, no write/update operations anywhere), but the stated data-access purpose is well served.