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security_audit_sbom_vulnerabilities

Read-onlyIdempotent

Audit a Software Bill of Materials (SBOM) to discover known vulnerabilities across all packages. Returns CVEs with severity and fixed versions for CycloneDX or SPDX JSON input.

Instructions

Audit a Software Bill of Materials for known vulnerabilities across all listed packages. Read-only. No side effects. Idempotent. sbom_json: CycloneDX or SPDX SBOM as a JSON string. Required. Large SBOMs (100+ packages) may take up to 10 seconds. Returns CVEs grouped by package with severity and fixed versions. Use this when you have a full SBOM to audit. Use security_fetch_package_vulnerabilities instead when checking a single package version. Verified source: Google OSV.dev batch API. 1-hour cache. 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_vulnerabilities", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sbom_jsonYesCycloneDX or SPDX SBOM as JSON string. Required.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint false, idempotentHint, and openWorldHint. The description adds useful context: 'Large SBOMs (100+ packages) may take up to 10 seconds. Returns CVEs grouped by package with severity and fixed versions. Verified source: Google OSV.dev batch API. 1-hour cache.' This enhances transparency beyond 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 concise and well-structured, with purpose, behavior, parameter, usage, and feedback all covered in a few efficient sentences. No wasted words.

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 complexity of SBOM auditing, the description comprehensively covers purpose, usage, parameter format, performance caveats, return structure, source verification, caching, and fallback. Output schema exists, so no need to detail return types.

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 coverage is 100% for the single parameter sbom_json. The description adds minimal value by specifying accepted formats (CycloneDX or SPDX), but largely repeats schema info. Baseline 3 is appropriate.

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 purpose: 'Audit a Software Bill of Materials for known vulnerabilities across all listed packages.' It specifies the resource (SBOM) and action, and distinguishes from sibling security_fetch_package_vulnerabilities by noting the former is for full SBOMs.

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?

Explicit usage guidance is provided: 'Use this when you have a full SBOM to audit. Use security_fetch_package_vulnerabilities instead when checking a single package version.' It also includes a fallback feedback mechanism for incomplete results.

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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