analyzing-sbom-for-supply-chain-vulnerabilities

Parses Software Bill of Materials (SBOM) in CycloneDX and SPDX JSON formats to identify supply chain vulnerabilities by correlating components against the NVD CVE database via the NVD 2.0 API. Builds dependency graphs, calculates risk scores, identifies transitive vulnerability paths, and generates compliance reports. Activates for requests involving SBOM analysis, software composition analysis, supply chain security assessment, dependency vulnerability scanning, CycloneDX/SPDX parsing, or CVE correlation.

Quality

86%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

72%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Highly actionable content with strong executable examples, but the workflow lacks explicit validation/retry checkpoints for a batch scanning operation, and progressive disclosure is underused: existing bundle files are unreferenced while reusable material is inlined.

Suggestions

Add explicit validation/retry checkpoints to the workflow—e.g., handle NVD rate limits (403/503) with backoff and a verify-before-report step—so the batch operation can score above 3 on workflow clarity.

Reference the existing bundle from the body (e.g., 'See references/api-reference.md for full NVD endpoint parameters' and 'scripts/agent.py for a complete reference implementation') and move the sample report template and Key Concepts table into separate reference files.

Trim the Key Concepts definitions for SBOM/NVD/CPE/PURL that Claude already knows, keeping only SBOM-format-specific nuances.

Dimension	Reasoning	Score
Conciseness	Largely efficient with focused code blocks, but includes minor over-explanation Claude already knows (Key Concepts table defining SBOM/NVD/CPE, ecosystem lists) and a verbose sample report template that could be trimmed.	4 / 5
Actionability	Provides copy-paste-ready, executable bash and Python code covering the common cases—syft generation, NVD API queries, networkx graph building, grype scanning—each complete with imports and real endpoints.	5 / 5
Workflow Clarity	Seven steps are clearly sequenced and cross-validation with grype provides one checkpoint, but this batch NVD-scanning operation lacks explicit validation/error-recovery loops (rate-limit handling, retry-on-failure, verify-before-report), which caps batch-operation workflow clarity per the rubric.	3 / 5
Progressive Disclosure	Bundle files exist (references/api-reference.md, scripts/agent.py) but are never referenced or signaled from the body, while large report templates, a Key Concepts table, and scenarios are inlined rather than split into separate files.	3 / 5
	Total	15 / 20 Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, third-person description that comprehensively states capabilities and explicit activation triggers with natural keywords. No significant gaps in specificity, completeness, or distinctiveness.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions—parsing CycloneDX/SPDX, correlating against NVD CVE, building dependency graphs, calculating risk scores, identifying transitive paths, generating compliance reports—covering the skill comprehensively.	5 / 5
Completeness	Explicitly answers both 'what' (parses SBOM, correlates with NVD, builds graphs, scores risk, generates reports) and 'when' via 'Activates for requests involving...' with concrete trigger phrases.	5 / 5
Trigger Term Quality	Comprehensive natural trigger phrases including synonyms: 'SBOM analysis, software composition analysis, supply chain security assessment, dependency vulnerability scanning, CycloneDX/SPDX parsing, or CVE correlation'.	5 / 5
Distinctiveness Conflict Risk	Clear niche in SBOM/supply-chain security with distinct, specific triggers that are unlikely to conflict with other skills.	5 / 5
	Total	20 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: mukul975/Anthropic-Cybersecurity-Skills
Path: skills/analyzing-sbom-for-supply-chain-vulnerabilities/SKILL.md
Commit: 9429fe9

Reviewed: 2 days ago

Table of Contents

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