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ContrastAPI

by com.contrastcyber

Bulk Sigma Rule Lookup

bulk_sigma_rule_lookup
Read-onlyIdempotent

Bulk Sigma rule lookup — retrieve full records for up to 50 rule UUIDs in a single request instead of N separate sigma_rule_lookup calls. Designed for triage workflows where multiple rule ids are known (e.g., from a SIEM alert batch or a tagged detection bundle). Each item is the same shape as sigma_rule_lookup with status ok/not_found/invalid_format and an error field when applicable. Up to 50 rule ids per call (same cap for Free and Pro). Each rule_id consumes 1 unit of the hourly quota; ids beyond the caller's remaining quota land in skipped_due_to_rate_limit instead of failing the whole batch (parity with bulk_cve/ioc). Free: 30/hr, Pro: 500/hr. Returns {results [{rule_id, status, rule, error}], total, processed, skipped_due_to_rate_limit, successful, failed, partial, summary, next_calls}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rule_idsYesList of Sigma rule UUIDs in RFC 4122 format. Up to 50 per call (same cap for Free and Pro). Each rule_id counts as 1 request toward the hourly quota. Per-item validation: invalid-format ids return status='invalid_format', unknown UUIDs return status='not_found' — the whole call does not fail.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.7/5.0
Behavior5/5

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

Beyond annotations (readOnly, idempotent), the description discloses per-item status handling (ok/not_found/invalid_format), quota consumption per rule_id, graceful degradation via skipped_due_to_rate_limit, Free/Pro limits, and the exact return structure—substantially exceeding the baseline.

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 compact yet rich, front-loaded with purpose, and every sentence conveys essential information without 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?

With a complete schema, output schema, and annotations, plus detailed rate-limit and error-handling context, the description leaves no significant gaps for an agent to misuse the tool.

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?

The schema already fully documents rule_ids (format, max 50, per-item validation, quota). The description adds no new parameter-level semantics; it mostly repeats or discusses output behavior, so baseline 3 applies.

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 explicitly states it retrieves full records for up to 50 rule UUIDs in a single request, and contrasts with sigma_rule_lookup, making its purpose unambiguous and distinguishing it from siblings.

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

Usage Guidelines5/5

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

It provides explicit guidance: designed for triage workflows where multiple rule ids are known, and positioned as an alternative to N separate sigma_rule_lookup calls. It also notes parity with bulk_cve/ioc for rate-limit behavior, helping the agent decide when to use it.

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.

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