Agent skill

ln-640-pattern-evolution-auditor

Audits architectural patterns against best practices, maintains patterns catalog with compliance scores. Use when auditing pattern evolution.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill ln-640-pattern-evolution-auditor-levnikolaevich-claude-code-skil --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 23 KB
Bundled scripts: none
Path: skills/analysis/ln-640-pattern-evolution-auditor-levnikolaevich-claude-code-skil/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

Review
written from the skill's own SKILL.md · Aug 5, 2026

What it does

Audits architectural patterns against best practices, maintains a patterns catalog with compliance scores. Use when auditing pattern evolution.

How it works

  • The skill orchestrates a multi-phase pattern evolution audit, relying on a core 4-score model (Compliance, Completeness, Quality, Implementation) with a 70% threshold. It coordinates several worker components (ln-641 to ln-647) in Phase 4, with ln-641 scored in Phase 5, and uses mandatory reads from shared references to guide detection, validation, and aggregation.
  • Phase 1a Baseline Detection loads and reconciles docs/project/patterns_catalog.md, ensures required sections exist, links ADRs and Guides, and auto-detects patterns in the pattern library as baseline.
  • Phase 1b Adaptive Discovery extends the catalog with patterns discovered from structural and document-based heuristics, returning per-pattern evidence and marking them as Discovered Patterns (Adaptive).
  • Phase 1c Pattern Recommendations add advisory patterns to the catalog under a dedicated section.
  • Phase 1d Applicability Verification checks that detected patterns have sufficient components, plus semantic verification via MCP Ref and WebSearch, and updates catalog sections for Excluded or Verified statuses.
  • Phase 2+ involve best-practices research, domain setup, and a multi-worker audit (Phase 4) across potential domains, followed by Phase 5 per-pattern analysis (ln-641).
  • Phase 6 performs cross-domain aggregation by parsing worker outputs (642–647), identifying systemic issues, and proposing architectural fixes.
  • Phase 7 Gap Analysis enumerates undocumented patterns, missing components, layer violations, consistency issues, and systemic issues.
  • Aggregation and reporting rely on templates and core contracts defined in shared references (audit_worker_core_contract.md, audit_worker_report_template.md) and produce per-worker JSON-like reports in designated output paths.

When to use it

Use when auditing pattern evolution, ensuring patterns_catalog.md is up-to-date, and when you need cross-domain and domain-aware insights about pattern compliance, quality, and potential systemic issues.

What it can touch

  • Worker orchestration uses agents to invoke these skills: ln-641-pattern-analyzer, ln-642-layer-boundary-auditor, ln-643-api-contract-auditor, ln-644-dep-graph-auditor, ln-645-open-source-replacer, ln-646-project-structure-auditor, ln-647-env-config-auditor. It relies on shared references and templates for evaluation and reporting.

Caveats

  • Requires loading mandatory references and templates (e.g., shared/references/task_delegation_pattern.md, two_layer_detection.md, scoring_rules.md, audit_coordinator_domain_mode.md).__n- Outputs are file-based reports with standardized naming per worker (e.g., 641-pattern-{slug}.md, 642-layer-boundary[-{domain}].md, etc.).
From the SKILL.md

> **Paths:** File paths (`shared/`, `references/`, `../ln-*`) are relative to skills repo root. If not found at CWD, locate this SKILL.md directory and go up one level for repo root. If `shared/` is missing, fetch files via WebFetch from `https://raw.githubusercontent.com/levnikolaevich/claude-code-skills/master/skills/{path}`. # Pattern Evolution Auditor L2 Coordinator that analyzes implemented architectural patterns against current best practices and tracks evolution over time. ## Purpose & Scope - Maintain `docs/project/patterns_catalog.md` with implemented patterns - Research best practices via MCP Ref, Context7, WebSearch - Audit layer boundaries via ln-642 (detect violations, check coverage) - Calculate 4 scores per pattern via ln-641 - Track quality trends over time (improving/stable/declining) - Output: `docs/project/patterns_catalog.md` (file-based) ## 4-Score Model | Score | What it measures | Threshold | |-------|------------------|-----------| | **Compliance** | Industry standards, naming, tech stack conventions, layer boundaries | 70% | | **Completeness** | All components, error handling, observability, tests | 70% | | **Quality** | Readability, maintainability, no sme

What's inside
Steps it walks through
  1. Purpose & Scope
  2. 4-Score Model
  3. Worker Invocation
  4. Workflow
  5. Phase 1a: Baseline Detection
  6. Phase 1b: Adaptive Discovery
  7. Phase 1c: Pattern Recommendations
  8. Phase 1d: Applicability Verification
  9. Phase 2: Best Practices Research
  10. Phase 3: Domain Discovery + Output Setup
  11. Phase 4: Layer Boundary + API Contract + Dependency Graph Audit
  12. Phase 5: Pattern Analysis Loop
  13. Phase 6: Cross-Domain Aggregation (File-Based)
  14. Phase 7: Gap Analysis
Ships with 1 file
  • metadata.json
Commands it runs
rm -rf {output_dir}
More from claude-skill-registry
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About this skill
What does the ln-640-pattern-evolution-auditor skill do?

Audits architectural patterns against best practices, maintains patterns catalog with compliance scores. Use when auditing pattern evolution.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill ln-640-pattern-evolution-auditor-levnikolaevich-claude-code-skil --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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