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ContrastAPI

by com.contrastcyber

Bulk ATLAS Technique Lookup

bulk_atlas_technique_lookup
Read-onlyIdempotent

Bulk ATLAS technique lookup — retrieve full records for up to 50 techniques in a single request instead of N separate atlas_technique_lookup calls. Designed as the natural follow-up to atlas_case_study_lookup, whose techniques_used array can be passed directly. Each item is the same shape as atlas_technique_lookup, including parent-tactics inheritance for sub-techniques (inherited_tactics=true flag) and per-item next_calls (D3FEND bridge when attack_reference_id present, sibling-technique search by tactic, parent lookup for sub-techniques). Free: 30/hr (1 per item), Pro: 500/hr. Returns {results [{technique_id, status (ok|not_found|invalid_format), technique, error}], total, successful, failed, partial, summary}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
technique_idsYesList of MITRE ATLAS technique ids in format 'AML.T####' or 'AML.T####.###' (e.g. ['AML.T0051', 'AML.T0043', 'AML.T0000.000']). Up to 50 per call. Case-insensitive; normalized + de-duplicated server-side. Each id counts as 1 request toward the rate limit.

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?

Despite annotations already declaring readOnly/idempotent/destructive flags, the description enriches behavior with per-item details: 'parent-tactics inheritance... inherited_tactics=true flag,' 'per-item next_calls' with D3FEND/sibling/parent options, and the response envelope including partial-failure statuses. This goes well beyond structured metadata.

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?

Though long, the description front-loads the core purpose in the first clause and then packs each subsequent sentence with necessary detail (per-item shape, next_calls, rate limits, return structure). No filler; the length is justified by the tool's complexity.

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 description covers the full usage lifecycle: when to use, input constraints, per-item result shape with error statuses, follow-up actions from next_calls, rate limits, and the top-level response fields. With output schema and annotations present, nothing critical is missing.

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 covers technique_ids with format, max, case-insensitivity, normalization/de-dup, and per-item rate count (100% coverage). The description does not add new param semantics beyond restating the 50-technique limit, so baseline of 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?

Clearly states 'retrieve full records for up to 50 techniques in a single request' and contrasts with 'N separate atlas_technique_lookup calls,' distinguishing it from the sibling single-lookup tool. Also names the natural predecessor (atlas_case_study_lookup), making the purpose concrete.

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?

Explicitly frames it as 'instead of N separate atlas_technique_lookup calls' and as 'the natural follow-up to atlas_case_study_lookup,' telling the agent when to choose this bulk tool. Also notes rate-limit implications (1 per item), helping with batch planning.

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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