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variant-analysis

Find similar vulnerabilities and bugs across codebases using pattern-based analysis. Use when hunting bug variants, building CodeQL/Semgrep queries, analyzing security vulnerabilities, or performing systematic code audits after finding an initial issue.

70

Quality

86%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is variant-analysis in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

81%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.

The body is a well-structured, actionable methodology with a standout iterative workflow that includes real validation and feedback loops. It is held back from the top tier by minor verbosity, a placeholder search example, and progressive-disclosure references that point to files not actually bundled here.

Suggestions

Replace the placeholder `rg -n "exact_vulnerable_code_here"` with a realistic worked example (or inline one of the referenced Semgrep/CodeQL query templates) so the core instruction is copy-paste executable without leaving SKILL.md.

Tighten the 'Critical Pitfalls' section by collapsing the repeated Example+Mitigation structure into a single line each, or move it into METHODOLOGY.md to keep SKILL.md as a lean overview.

Add 'static analysis' / 'SAST' to the description trigger terms and confirm the referenced METHODOLOGY.md and resources/ files are bundled so the progressive-disclosure navigation is resolvable.

DimensionReasoningScore

Conciseness

The body is efficient and assumes Claude's competence (it never explains what CodeQL, Semgrep, or a vulnerability is), using tables to compress information; minor over-explanation remains in the tool-selection 'Why' column and the repetitive Example/Mitigation phrasing of the pitfalls section, keeping it just below anchor 5.

4 / 5

Actionability

Provides a concrete five-step process, an abstraction-points table, a tool-selection table, and an executable `rg -n` command, but the ripgrep example is a placeholder and the real CodeQL/Semgrep query templates are deferred to un-bundled `resources/` files, leaving minor gaps versus fully copy-paste-ready anchor 5.

4 / 5

Workflow Clarity

The five-step process is clearly sequenced with an explicit validation checkpoint ('Verify: Does it match exactly ONE location?') and a genuine feedback loop in Step 4 (run, review all matches, classify TP/FP, revert if FP rate too high, stop at ~50%), plus a triage checklist in Step 5, matching anchor 5; the operation is read-only so the destructive-cap does not apply.

5 / 5

Progressive Disclosure

Well-organized into clear sections with one-level-deep, clearly signaled references ('see METHODOLOGY.md', 'Ready-to-use templates in resources/'), but no bundle files are present to verify those references against and a fair amount of inline content (Critical Pitfalls, Key Principles) could arguably live in METHODOLOGY.md, so it sits below the clean split of anchor 5.

4 / 5

Total

17

/

20

Passed

Description

92%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.

The description is specific, complete, and distinct: it states concrete capabilities and pairs them with an explicit 'Use when' trigger clause rich in natural security-audit terms. Its only soft spot is trigger-term breadth, where a few common synonyms (static analysis, SAST) are absent.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ('Find similar vulnerabilities and bugs', 'hunting bug variants', 'building CodeQL/Semgrep queries', 'analyzing security vulnerabilities', 'performing systematic code audits') with comprehensive coverage of the variant-analysis domain, matching the anchor 5 example.

5 / 5

Completeness

Clearly answers both 'what' ('Find similar vulnerabilities and bugs across codebases using pattern-based analysis') and 'when' with an explicit 'Use when...' clause carrying concrete trigger phrases, matching anchor 5 exactly.

5 / 5

Trigger Term Quality

Strong natural trigger terms a security analyst would say ('CodeQL', 'Semgrep', 'bug variants', 'security vulnerabilities', 'code audits') plus synonyms (vulnerabilities/bugs), but a few natural terms like 'static analysis', 'SAST', or 'taint analysis' are missing, placing it just below the comprehensive anchor 5.

4 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (variant analysis after an initial issue is found) with distinct tool-based triggers (CodeQL/Semgrep) and an 'after finding an initial issue' framing that sharply separates it from discovery, review, and fix skills, giving minimal conflict risk.

5 / 5

Total

19

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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