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ASN Lookup

asn_lookup
Read-onlyIdempotent

Look up Autonomous System Number (ASN) for a domain or IP: AS number, organization, IPv4/IPv6 prefixes. Use to identify network operator and IP range ownership. Default returns first 50 prefixes per family — set include_full_prefixes=True for full list. Free: 30/hr, Pro: 500/hr. Returns {asn, asn_name, ipv4_prefixes, ipv6_prefixes, ipv4_count, ipv6_count}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYesDomain or IP address to look up ASN for (e.g. 'cloudflare.com', '8.8.8.8')
include_full_prefixesNoReturn the full announced-prefixes list (default: False, returns first 50). ipv4_count and ipv6_count are always honest pre-truncation totals. Set True for network mapping or BGP route audits — Cloudflare AS13335 announces 2500+ prefixes.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite annotations already flagging readOnlyHint, idempotentHint, and destructiveHint, the description adds important behavioral details: default prefix truncation to 50 per family, the availability of include_full_prefixes to get the full list, and rate limits ('Free: 30/hr, Pro: 500/hr'). It also clarifies that ipv4_count/ipv6_count are honest pre-truncation totals. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and efficient. It opens with the purpose, then use case, then behavioral details (truncation, rate limits), and closes with the return shape. Every sentence adds value; no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple (2 params, 1 required) and has an output schema per context signals. The description covers purpose, use case, parameter behavior, rate limits, and return fields, providing everything an agent needs to select and invoke the tool correctly. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description reinforces parameter behavior (e.g., 'set include_full_prefixes=True for full list') but does not add meaning beyond what the schema already provides for each parameter. The return-object mention offers slight context, but parameters are fully documented in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Look up Autonomous System Number (ASN) for a domain or IP' and specifies the returned data (AS number, organization, IPv4/IPv6 prefixes). It distinguishes itself from sibling tools like ip_lookup or whois_lookup by focusing on ASN and network ownership, using a specific verb+resource structure.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear use case: 'Use to identify network operator and IP range ownership.' This gives context for when to use the tool, though it does not explicitly mention when not to use it or name alternative tools. That fits the 'clear context, no exclusions' level.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.5/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with differences between lookup/search/scan/audit for each domain. However, some overlap exists (e.g., email_mx vs email_security_posture, scan_headers vs contrast_scan) which could cause occasional confusion. Overall, boundaries are well-defined.

Naming Consistency5/5

Tool names follow a consistent verb_noun pattern (e.g., cve_lookup, check_headers, bulk_cve_lookup) with all lowercase underscores. Variations like kev_detail or ssl_check are minor and still predictable. No chaotic mixing of conventions.

Tool Count4/5

54 tools is high but justified by the broad cybersecurity scope (CVE, ATLAS, D3FEND, Sigma, domain, email, IOC, scanning). Some redundancy exists (e.g., three email-related tools), but the count is not excessive given the API's comprehensive feature set.

Completeness5/5

The tool set thoroughly covers the threat intelligence and domain investigation lifecycle: CVE/KEV/exploit/CWE, ATLAS/D3FEND/Sigma, DNS/WHOIS/SSL/subdomains, email security, IOC enrichment, and active scanning. No significant gaps are apparent for the stated cybersecurity purpose.