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arn-code-batch-cve-scan

This skill should be used when the user says "scan for CVEs", "CVE scan", "check for vulnerabilities", "dependabot triage", "audit dependencies", "security scan", "arness CVE scan", "arn-code-batch-cve-scan", "run a scheduled CVE scan", "finalize a CVE proposal", or wants Arness to discover, triage, and ticket security advisories across project dependencies (GitHub Dependabot plus locally-detected scanners). Three modes: interactive, proposal (unattended, safe for Routines or claude -p), and finalize (review a proposal and file tickets on GitHub or Jira).

Quality

91%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

85%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.

A well-engineered sequencer SKILL.md: lean step summaries, concrete commands for the steps that stay inline, thorough validation gates appropriate to a batch ticket-writing operation, and a clean one-level-deep reference structure with all 11 referenced files present. The residual costs are mild restating of the modes.md contract inside the body and one step (Step 8) that keeps procedural detail inline without a concrete query example.

Suggestions

Trim the per-mode restatements in Steps 2, 3, and 9b to a one-line mode note (e.g. "mode-aware; see modes.md for the contract") since modes.md is already declared canonical, removing the duplication risk if the contract ever changes.

Give Step 8 a concrete example of the issue query and dedupe key application (e.g. an actual gh/Jira search command or a two-line example of matching an advisory-id against the open-ticket set), or move its procedure into ticketing.md like the other procedural steps.

The Step 0 bullet list of extracted fields could be compressed into a table or left to the ensure-config reference it already defers to, saving body tokens without losing information.

DimensionReasoningScore

Conciseness

The body is an efficient sequencer — each step is a few lines pointing at a reference file — but there is minor duplication: per-mode rules are restated in Steps 2, 3, and 9b even though modes.md is declared the canonical contract, and the Step 0 field list slightly restates what ensure-config already guarantees. This matches the "minor instances of over-explanation that could be trimmed" anchor rather than the every-token-earns-its-place anchor at 5.

4 / 5

Actionability

Steps kept inline carry concrete, executable commands ("git ls-remote --exit-code origin \"<security-branch>\"", "git symbolic-ref --short refs/remotes/origin/HEAD", "sha256sum || shasum -a 256", the exact "arness::cve-scan::proposal-ready path=" line format, and a copy-paste claude -p invocation), and every step names its reference file explicitly. It falls short of 5 because Step 8's issue-query/dedupe logic remains in the body with no concrete command or example query, leaving a small execution gap.

4 / 5

Workflow Clarity

The 11-step pipeline is explicitly sequenced with mode-branching called out per step, and this batch write operation has real validation checkpoints: hard stop conditions in Step 0, the stale-DB gate in Step 2, branch existence validated via exit-code-checked git ls-remote in Step 3, SHA-256 checksums proving input integrity in Step 6, an idempotency dedupe before any writes in Step 8, a single consent gate in finalize mode, and an ordered atomic-rename-then-completion-signal contract in Step 10. This matches the explicit-validation-with-checkpoints anchor.

5 / 5

Progressive Disclosure

The skill declares itself a sequencer that "MUST NOT duplicate sub-reference logic" and delivers on it: the body is a navigable index that names each step and points to one of 11 real, one-level-deep reference files (all verified present in references/), each signaled with a full path, plus a pipeline diagram showing where the skill sits. This matches the clear-overview-with-well-signaled-one-level-deep-references anchor.

5 / 5

Total

18

/

20

Passed

Description

96%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 description: it answers what (discover, triage, ticket security advisories across dependencies from two named sources) and when (explicit trigger-phrase list plus unattended/scheduled variants) in third person, with the three modes concisely characterized. The only weakness is that a few broad trigger phrases ("security scan", "check for vulnerabilities") could collide with adjacent security skills.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "discover, triage, and ticket security advisories across project dependencies" — and specifies both sources ("GitHub Dependabot plus locally-detected scanners") and the three modes with their concrete behaviors ("review a proposal and file tickets on GitHub or Jira"), which matches the comprehensive-coverage anchor rather than the minor-gaps anchor at 4.

5 / 5

Completeness

Both halves are explicit: the what is "discover, triage, and ticket security advisories across project dependencies" and the when is "This skill should be used when the user says..." with a list of concrete trigger phrases, exactly matching the anchor for clearly answering both what and when.

5 / 5

Trigger Term Quality

It enumerates natural phrases users would actually say — "scan for CVEs", "CVE scan", "check for vulnerabilities", "dependabot triage", "audit dependencies", "security scan", "run a scheduled CVE scan", "finalize a CVE proposal" — covering synonyms and scheduled/headless variants, matching the comprehensive-coverage anchor.

5 / 5

Distinctiveness Conflict Risk

The CVE/dependency-advisory triage-and-ticketing niche is distinct and the skill name triggers ("arness CVE scan", "arn-code-batch-cve-scan") are unique, but broad triggers like "security scan" and "check for vulnerabilities" carry minor overlap risk with a generic code-security-audit skill, so it sits at mostly-distinct rather than minimal-conflict.

4 / 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.

Validation — 15 / 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

AppsVortex/arness

Path

plugins/arn-code/skills/arn-code-batch-cve-scan/SKILL.md

Reviewed

Table of Contents

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