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production-code-audit

Autonomously deep-scan entire codebase line-by-line, understand architecture and patterns, then systematically transform it to production-grade, corporate-level professional quality with optimizations

Quality

49%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/production-code-audit/SKILL.md

The canonical home for this skill is production-code-audit in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

31%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 skill has a clear high-level sequence and some concrete thresholds, but it is severely bloated: it re-enumerates standard vulnerability and quality knowledge Claude already has, inlines simulated output transcripts with fabricated metrics, and keeps everything in one 535-line file with no reference structure. The batch-fix workflow also lacks any failure/recovery feedback loop.

Suggestions

Cut the ~170 lines of simulated example transcripts (fabricated issue counts, metrics, and Lighthouse scores) and the lists of well-known vulnerability types; keep only guidance Claude would not generate on its own, such as the project-specific thresholds and prioritization rules.

Move the audit report template, the long checklists, and the detailed fix examples into separate reference files (e.g. references/report-template.md, references/checklists.md) and link them from a lean SKILL.md overview.

Add an explicit validation feedback loop for the batch-fix workflow: after each fix category run the test suite, and if tests fail, revert or repair the change before proceeding — rather than only a single 'run all tests' step at the end.

DimensionReasoningScore

Conciseness

The 535-line body extensively catalogs issues Claude already knows (SQL injection, N+1 queries, XSS, hardcoded secrets, TODO/FIXME comments) and devotes ~170 lines to simulated output transcripts with fabricated metrics ("analyzing 247 files", "Lighthouse 62 → 94", "42% → 87% coverage") that provide no actionable instruction — severely verbose and heavily padded.

1 / 5

Actionability

There are some concrete signals (god classes >500 lines or >20 methods, complexity >10, bcrypt 12 rounds, coverage >80%, before/after code diffs), but the core workflow is described rather than instructed ("Fix everything automatically", "Use `strReplace` to fix issues in files") with no executable commands or tool specifics for the scan/fix loop.

3 / 5

Workflow Clarity

Steps 1–4 provide a clear Discover → Detect → Fix → Verify sequence and Step 4 says "Run all tests to ensure nothing broke", but this is a large batch of code modifications (~89 files in the example) with no feedback loop — no guidance for what to do when tests fail, no per-fix verification, and no rollback strategy, capping workflow clarity at 3 per the batch-operation guideline.

3 / 5

Progressive Disclosure

No bundle files exist and the body contains no file references at all; ~250 lines of example transcripts, a 40-line report template, and full audit checklists are all inlined in a single monolithic SKILL.md where they clearly belong in separate reference files — content that clearly belongs in separate files is inlined.

2 / 5

Total

9

/

20

Passed

Description

46%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 communicates a broad code-quality transformation intent but is padded with buzzwords, lacks any "use when" trigger guidance, and doesn't include the natural phrases users would say to invoke it. It also overlaps with many existing code-review and optimization skills.

Suggestions

Add an explicit 'Use when...' clause with natural trigger phrases, e.g. 'Use when the user says make this production-ready, audit my codebase, or harden this code for deployment.'

Replace buzzword padding ('corporate-level professional quality with optimizations') with specific concrete actions such as 'fix security vulnerabilities, resolve N+1 queries, refactor god classes, and add tests, logging, and health checks.'

Narrow the scope or add distinct trigger terms to differentiate it from general code-review, refactoring, and performance-optimization skills.

DimensionReasoningScore

Specificity

The description names the domain and three actions ("deep-scan entire codebase line-by-line", "understand architecture and patterns", "transform it to production-grade"), but the actions are generic and padded with buzzwords like "corporate-level professional quality" and "with optimizations" rather than specific concrete capabilities.

3 / 5

Completeness

The "what" is clearly stated (scan, understand, transform the codebase), but there is no "Use when..." clause or equivalent trigger guidance, which caps completeness at 3 per the rubric guidelines.

3 / 5

Trigger Term Quality

"production-grade", "corporate-level", and "optimizations" are relevant keywords, but the natural phrases users would actually say ("make this production-ready", "audit my code", "refactor my codebase") are missing, and "deep-scan line-by-line" is jargon rather than user speech.

3 / 5

Distinctiveness Conflict Risk

Broad terms like "entire codebase", "professional quality", and "optimizations" overlap heavily with code-review, refactoring, and performance-optimization skills, with no distinct trigger separating it from them — very broad with high overlap risk.

2 / 5

Total

11

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (544 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

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

Warning

Total

14

/

16

Passed

Repository

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills-claude/skills/production-code-audit/SKILL.md

Reviewed

Table of Contents

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