DataNexus MCP

security_audit_sbom_license_policy

Read-onlyIdempotent

Audit a CycloneDX or SPDX SBOM against an SPDX licence policy and return a PASS/WARN/BLOCK verdict. sbom: Full SBOM as a JSON string — CycloneDX or SPDX format. Required. 500 KB max. policy: Optional dict with block/warn/allow arrays of exact SPDX licence identifiers (e.g. GPL-3.0, MIT). Defaults to block GPL-3.0 and AGPL-3.0, warn LGPL-2.1/MPL-2.0/BSD-4-Clause, allow MIT/Apache-2.0/BSD-2-Clause/BSD-3-Clause. No glob patterns — exact SPDX IDs only. Unlisted licences default to WARN. Returns verdict (PASS/WARN/BLOCK), blocked_packages, warned_packages, and the policy applied. Use security_audit_sbom_vulnerabilities for CVE auditing instead. Sources: deps.dev (Google). 1-hour cache per package. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="security_audit_sbom_license_policy", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Input Schema

TableJSON Schema

Name	Required	Description	Default
`sbom`	Yes	CycloneDX or SPDX SBOM as JSON string. Required. 500 KB max.
`policy`	No	Policy dict with block/warn/allow arrays of SPDX licence IDs. Optional.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.9/5.0

Behavior5/5

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

Beyond annotations (readOnly, idempotent), the description discloses constraints (500 KB max, exact SPDX IDs only), default policy behavior, unlisted license handling (default WARN), caching (1-hour), and data source (deps.dev), providing comprehensive behavioral context.

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

Conciseness4/5

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

The description is dense but well-organized, with purpose first, then parameters, returns, alternatives, and miscellany. Every sentence adds value, though slightly verbose for the most concise possible version.

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?

Given the tool's complexity and the presence of an output schema, the description covers all necessary aspects: input constraints, default policies, return structure, caching, source, and feedback mechanism, leaving no critical gaps.

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

Parameters5/5

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

With 100% schema coverage, the description adds significant value by specifying format requirements (CycloneDX or SPDX JSON), size limit, policy default structure, exact ID requirement, and return fields, far exceeding the baseline.

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 the tool audits a CycloneDX or SPDX SBOM against a license policy and returns a PASS/WARN/BLOCK verdict, clearly differentiating it from sibling tools like security_audit_sbom_vulnerabilities.

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?

The description explicitly directs users to use security_audit_sbom_vulnerabilities for CVE auditing instead, and provides a fallback procedure via report_feedback if the response is inadequate.

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

A4.1/5.0

Disambiguation4/5

Tools are grouped into clear domain prefixes (compliance, domain, frontend_security, etc.) with distinct purposes. Minor overlap exists between frontend_security_detect_typosquatting and security_detect_typosquatting, but descriptions clarify the different scope.

Naming Consistency4/5

Most tools follow a consistent verb_noun pattern with snake_case. Irregularities like 'fetch' vs 'audit' and two 'detect_typosquatting' tools exist, but overall naming is predictable within domains.

Tool Count3/5

55 tools is high for a single server given the breadth of domains. Some redundancy (e.g., two typosquatting tools) suggests possible trimming, but the count is justified by the wide coverage.

Completeness4/5

The tool surface covers key operations across domains like compliance, domain, security, legal, and nonprofit. Minor gaps exist, such as limited frontend audit beyond package.json and no general-purpose code scanning.

Resources

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