Codebase Auditor (L2 Coordinator)

VerifiedCaution

Coordinates 9 specialized audit workers to perform comprehensive codebase analysis in parallel, researches best practices, and aggregates results into a consolidated report.

Sby Skills Guide Bot
DevelopmentAdvanced
3/4/2026
Claude Code
#code-audit#code-quality#parallel-workers#static-analysis#best-practices

Recommended for

Automated summary

Coordinates nine specialized audit workers to analyze codebase quality and consolidate their findings into a single report.

Strengths

  • Two-stage delegation runs global workers in parallel, then domain-aware workers based on detected project domains.
  • Applicability gate skips workers irrelevant to CLI tools, libraries, and scripts, marking them N/A in the report.
  • Performs stack-specific best-practice research once through MCP tools and shares context with all workers to save tokens.
  • Groups results by domain, calculates scores, and writes a consolidated report to docs/project/codebase_audit.md.

Limitations

  • Not standalone: assumes the nine ln-621 through ln-629 worker skills and the MCP Ref/context7 servers are available.
  • Writes to a fixed report path and does not create tasks or integrate with the Story pipeline.
  • Audit relevance depends on accurate metadata in docs/project/tech_stack.md and docs/principles.md.
When to use it

Use when you need a comprehensive multi-domain audit of an entire repository with one aggregated report.

When not to use it

Avoid for quick targeted reviews, or when the specialized audit skills and MCP documentation tools are not installed.

Security analysis

Caution
Quality score82/100

This is a read-oriented audit orchestrator. It uses powerful capabilities (Bash, network fetching, and subagent delegation) but only for legitimate research and report generation; there are no destructive commands, no secret/token exfiltration, no obfuscated payloads, and no attempts to disable safety. The residual risk comes from spawning general-purpose subagents and external network fetches, which warrants a caution rather than a clean 'safe'.

Findings
  • •Delegates execution to general-purpose subagents (Task tool) that inherit broad tool access; the coordinator does not constrain what the worker skills may do once invoked.
  • •Uses network egress (WebFetch, WebSearch, mcp__Ref, mcp__context7) to fetch external best-practice documentation for detected dependencies.
  • •Bash usage is limited to `mkdir -p {output_dir}` and file-globbing, which is benign.
  • •Overwrites `docs/project/codebase_audit.md` on each run (documented as an intentional full snapshot); per-run worker reports are preserved in dated folders.
  • •Uses Bash for filesystem operations and writes/overwrites `docs/project/codebase_audit.md` plus date-stamped audit output; legitimate but requires scoped execution.
  • •Uses WebFetch, WebSearch, and MCP documentation tools to retrieve external best-practice content, introducing normal network/data-fetching exposure.
  • •Delegates to general-purpose subagents that may read broad codebase content; context isolation is specified, but the orchestrator relies on external worker skills for the actual audit logic.
How this analysis is made

Examples

Full repository audit
Run a full codebase audit on this repository and write the consolidated report to docs/project/codebase_audit.md.
Stack-aware parallel audit
Research current best practices for our stack, decide which audit workers apply to this project, run the relevant audits in parallel, and summarize the scores by domain.
Service-focused audit
Audit our web service for security, build, architecture, code quality, dependencies, dead code, observability, concurrency, and lifecycle issues, then aggregate the findings into one report.

name: ln-620-codebase-auditor description: "Coordinates 9 specialized audit workers (security, build, architecture, code quality, dependencies, dead code, observability, concurrency, lifecycle). Researches best practices, delegates parallel audits, aggregates results into docs/project/codebase_audit.md." allowed-tools: Read, Grep, Glob, Bash, WebFetch, WebSearch, mcp__Ref, mcp__context7, Skill

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.

Codebase Auditor (L2 Coordinator)

Coordinates 9 specialized audit workers to perform comprehensive codebase quality analysis.

Purpose & Scope

  • Coordinates 9 audit workers (ln-621 through ln-629) running in parallel
  • Research current best practices for detected tech stack via MCP tools ONCE
  • Pass shared context to all workers (token-efficient)
  • Aggregate worker results into single consolidated report
  • Write report to docs/project/codebase_audit.md (file-based, no task creation)
  • Manual invocation by user; not part of Story pipeline

Workflow

  1. Discovery: Load tech_stack.md, principles.md, package manifests, auto-discover Team ID
  2. Worker Applicability: Determine project type, skip inapplicable workers
  3. Research: Query MCP tools for current best practices per major dependency ONCE
  4. Domain Discovery: Detect project domains from folder structure
  5. Delegate: Two-stage delegation - global workers (5a) + domain-aware workers (5b)
  6. Aggregate: Collect worker results, group by domain, calculate scores
  7. Write Report: Save to docs/project/codebase_audit.md

Phase 1: Discovery

Load project metadata:

  • docs/project/tech_stack.md - detect tech stack for research
  • docs/principles.md - project-specific quality principles
  • Package manifests: package.json, requirements.txt, go.mod, Cargo.toml
  • Auto-discover Team ID from docs/tasks/kanban_board.md

Extract metadata only (not full codebase scan):

  • Programming language(s)
  • Major frameworks/libraries
  • Database system(s)
  • Build tools
  • Test framework(s)

Phase 2: Worker Applicability Gate

Determine project type from tech_stack metadata and skip inapplicable workers.

Project type detection:

| Project Type | Detection | Skip Workers | |-------------|-----------|--------------| | CLI tool | No web framework, has CLI framework (Typer/Click/Commander/cobra/etc.) | ln-627 (health checks), ln-629 (graceful shutdown) | | Library/SDK | No entry point, only exports | ln-627, ln-629 | | Script/Lambda | Single entry, <500 LOC | ln-627, ln-628 (concurrency), ln-629 | | Web Service | Has web framework (Express/FastAPI/ASP.NET/Spring/etc.) | None — all applicable | | Worker/Queue | Has queue framework (Bull/Celery/etc.) | None |

Algorithm:

project_type = detect_from_tech_stack(tech_stack, package_manifests)
skipped_workers = APPLICABILITY_TABLE[project_type].skip
applicable_workers = ALL_WORKERS - skipped_workers

FOR EACH skipped IN skipped_workers:
  skipped.score = "N/A"
  skipped.reason = "Not applicable for {project_type} projects"

Skipped workers are NOT delegated. They get score "N/A" in report and are excluded from overall score calculation.

Phase 3: Research Best Practices (ONCE)

For each major dependency identified in Phase 1:

  1. Use mcp__Ref__ref_search_documentation for current best practices
  2. Use mcp__context7__get-library-docs for up-to-date library documentation
  3. Focus areas by technology type:

| Type | Research Focus | |------|----------------| | Web Framework | Async patterns, middleware, error handling, request lifecycle | | ML/AI Libraries | Inference optimization, memory management, batching | | Database | Connection pooling, transactions, query optimization | | Containerization | Multi-stage builds, security, layer caching | | Language Runtime | Idioms, performance patterns, memory management |

Build contextStore:

{
  "tech_stack": {...},
  "best_practices": {...},
  "principles": {...},
  "codebase_root": "...",
  "output_dir": "docs/project/.audit/ln-620/{YYYY-MM-DD}"
}

Phase 4: Domain Discovery

Purpose: Detect project domains from folder structure for domain-aware auditing.

Algorithm:

  1. Priority 1: Explicit domain folders

    • Check for: src/domains/*/, src/features/*/, src/modules/*/
    • Monorepo patterns: packages/*/, libs/*/, apps/*/
    • If found (>1 match) → use these as domains
  2. Priority 2: Top-level src/ folders*

    • List folders: src/users/, src/orders/, src/payments/
    • Exclude infrastructure: utils, shared, common, lib, helpers, config, types, interfaces, constants, middleware, infrastructure, core
    • If remaining >1 → use as domains
  3. Priority 3: Fallback to global mode

    • If <2 domains detected → domain_mode = "global"
    • All workers scan entire codebase (backward-compatible behavior)

Heuristics for domain detection:

| Heuristic | Indicator | Example | |-----------|-----------|---------| | File count | >5 files in folder | src/users/ with 12 files | | Structure | controllers/, services/, models/ present | MVC/Clean Architecture | | Barrel export | index.ts/index.js exists | Module pattern | | README | README.md describes domain | Domain documentation |

Output:

{
  "domain_mode": "domain-aware",
  "all_domains": [
    {"name": "users", "path": "src/users", "file_count": 45, "is_shared": false},
    {"name": "orders", "path": "src/orders", "file_count": 32, "is_shared": false},
    {"name": "shared", "path": "src/shared", "file_count": 15, "is_shared": true}
  ]
}

Shared folder handling:

  • Folders named shared, common, utils, lib, core → mark is_shared: true
  • Shared code audited but grouped separately in report
  • Does not affect domain-specific scores

Phase 5: Delegate to Workers

CRITICAL: All delegations use Task tool with subagent_type: "general-purpose" for context isolation.

Phase 5.0: Prepare Output Directory

Before delegating to workers:

1. mkdir -p {output_dir}   # No deletion — date folders preserve history
2. output_dir already set in contextStore (Phase 3)

Prompt template:

Task(description: "Audit via ln-62X",
     prompt: "Execute ln-62X-{worker}-auditor. Read skill from ln-62X-{worker}-auditor/SKILL.md. Context: {contextStore}",
     subagent_type: "general-purpose")

Anti-Patterns:

  • ❌ Direct Skill tool invocation without Task wrapper
  • ❌ Any execution bypassing subagent context isolation

Worker Output Contract (File-Based):

Workers write full report to {output_dir}/{worker_id}.md per shared/templates/audit_worker_report_template.md.

Workers return minimal summary in-context (~50 tokens):

Report written: docs/project/.audit/ln-620/{YYYY-MM-DD}/621-security.md
Score: 7.5/10 | Issues: 5 (C:0 H:2 M:2 L:1)

Coordinator extracts score/counts from return values. Full findings stay in files.

Unified Scoring Formula (all workers):

penalty = (critical × 2.0) + (high × 1.0) + (medium × 0.5) + (low × 0.2)
score = max(0, 10 - penalty)

Phase 5a: Global Workers (PARALLEL)

Global workers scan entire codebase (not domain-aware). Each writes report to {output_dir}/.

| # | Worker | Priority | What It Audits | Output File | |---|--------|----------|----------------|-------------| | 1 | ln-621-security-auditor | CRITICAL | Hardcoded secrets, SQL injection, XSS, insecure deps | 621-security.md | | 2 | ln-622-build-auditor | CRITICAL | Compiler/linter errors, deprecations, type errors | 622-build.md | | 5 | ln-625-dependencies-auditor | MEDIUM | Outdated packages, unused deps, custom implementations | 625-dependencies.md | | 6 | ln-626-dead-code-auditor | LOW | Dead code, unused imports/variables, commented-out code | 626-dead-code.md | | 7 | ln-627-observability-auditor | MEDIUM | Structured logging, health checks, metrics, tracing | 627-observability.md | | 8 | ln-628-concurrency-auditor | HIGH | Race conditions, async/await, resource contention | 628-concurrency.md | | 9 | ln-629-lifecycle-auditor | MEDIUM | Bootstrap, graceful shutdown, resource cleanup | 629-lifecycle.md |

Invocation (applicable workers in PARALLEL):

// Filter by Phase 2 applicability gate
applicable_global = [ln-621, ln-622, ln-625, ln-626, ln-627, ln-628, ln-629].filter(w => !skipped_workers.includes(w))

FOR EACH worker IN applicable_global:
  Task(description: "Audit via " + worker,
       prompt: "Execute " + worker + ". Read skill. Context: " + JSON.stringify(contextStore),
       subagent_type: "general-purpose")

Phase 5b: Domain-Aware Workers (PARALLEL per domain)

Domain-aware workers run once per domain. Each writes report with domain suffix.

| # | Worker | Priority | What It Audits | Output File | |---|--------|----------|----------------|-------------| | 3 | ln-623-code-principles-auditor | HIGH | DRY/KISS/YAGNI violations, TODO/FIXME, error handling, DI | 623-principles-{domain}.md | | 4 | ln-624-code-quality-auditor | MEDIUM | Cyclomatic complexity, O(n²), N+1 queries, magic numbers | 624-quality-{domain}.md |

Invocation (2 workers × N domains):

IF domain_mode == "domain-aware":
  FOR EACH domain IN all_domains:
    domain_context = {
      ...contextStore,
      domain_mode: "domain-aware",
      current_domain: { name: domain.name, path: domain.path }
    }
    Task(description: "Audit principles " + domain.name + " via ln-623",
         prompt: "Execute ln-623-code-principles-auditor. Read skill. Context: " + JSON.stringify(domain_context),
         subagent_type: "general-purpose")
    Task(description: "Audit quality " + domain.name + " via ln-624",
         prompt: "Execute ln-624-code-quality-auditor. Read skill. Context: " + JSON.stringify(domain_context),
         subagent_type: "general-purpose")
ELSE:
  // Fallback: invoke once for entire codebase (global mode)
  Task(description: "Audit principles via ln-623",
       prompt: "Execute ln-623-code-principles-auditor. Read skill. Context: " + JSON.stringify(contextStore),
       subagent_type: "general-purpose")
  Task(description: "Audit quality via ln-624",
       prompt: "Execute ln-624-code-quality-auditor. Read skill. Context: " + JSON.stringify(contextStore),
       subagent_type: "general-purpose")

Parallelism strategy:

  • Phase 5a: All applicable global workers run in PARALLEL
  • Phase 5b: All (2 × N) domain-aware invocations run in PARALLEL
  • Example: 3 domains → 6 invocations (ln-623×3 + ln-624×3) in single message

Phase 6: Aggregate Results (File-Based)

Workers wrote reports to {output_dir}/ and returned minimal summaries. Aggregation uses return values for numbers and file reads for findings tables.

Step 6.1: Parse Return Values

Extract score/counts from worker return strings (already in context, 0 file reads):

FOR EACH worker_return IN worker_results:
  Parse: "Score: {score}/10 | Issues: {total} (C:{c} H:{h} M:{m} L:{l})"
  Store: {worker, category, score, counts, report_file}

Step 6.2: Build Compliance Score Table

From parsed return values:

FOR EACH category IN 9 categories:
  IF category is domain-aware (Architecture, Quality):
    category_score = average(domain_scores for this category)
  ELSE:
    category_score = worker_score
overall_score = average(all applicable category scores)  // exclude N/A

Step 6.3: Build Severity Summary

From parsed return values:

total_critical = sum(worker.counts.critical for all workers)
total_high = sum(worker.counts.high for all workers)
total_medium = sum(worker.counts.medium for all workers)
total_low = sum(worker.counts.low for all workers)

Step 6.4: Build Domain Health Summary (if domain-aware)

From parsed return values of ln-623/ln-624:

FOR EACH domain:
  arch_score = ln-623 score for this domain
  quality_score = ln-624 score for this domain
  issues = ln-623 issues + ln-624 issues for this domain

Step 6.5: Cross-Domain DRY Analysis (if domain-aware)

Read only ln-623 report files to extract FINDINGS-EXTENDED JSON block:

principle_files = Glob("{output_dir}/623-principles-*.md")
FOR EACH file IN principle_files:
  Read file → extract <!-- FINDINGS-EXTENDED [...] --> JSON
  Filter findings with pattern_signature field

Group by pattern_signature across domains:
  IF same signature in 2+ domains → create Cross-Domain DRY finding:
    severity: HIGH
    principle: "Cross-Domain DRY Violation"
    list all affected domains and locations
    recommendation: "Extract to shared/ module"

Step 6.6: Assemble Findings Sections

Read each worker report file and copy Findings table into corresponding report section:

FOR EACH report_file IN Glob("{output_dir}/6*.md"):
  Read file → extract "## Findings" table rows
  Insert into matching category section in final report

Global categories (Security, Build, etc.) → single Findings table per category. Domain-aware categories → subtables per domain (one per file).

Step 6.7: Context Validation (Post-Filter)

MANDATORY READ: Load shared/references/context_validation.md

Apply Rules 1-5 to assembled findings. Uses data already in context:

  • ADR list (loaded in Phase 1 from docs/reference/adrs/ or docs/decisions/)
  • tech_stack metadata (Phase 1)
  • Worker report files (already read in Step 6.6)
FOR EACH finding IN assembled_findings WHERE severity IN (HIGH, MEDIUM):
  # Rule 1: ADR/Planned Override
  IF finding matches ADR title/description → advisory "[Planned: ADR-XXX]"

  # Rule 2: Trivial DRY
  IF DRY finding AND duplicated_lines < 5 → remove finding

  # Rule 3: Cohesion (god_classes, long_methods, large_file)
  IF size-based finding:
    Read flagged file ONCE, check 4 cohesion indicators
    IF cohesion >= 3 → advisory "[High cohesion module]"

  # Rule 4: Already-Latest
  IF dependency finding: cross-check ln-622 audit output
    IF latest + 0 CVEs → remove finding

  # Rule 5: Locality/Single-Consumer
  IF DRY/schema finding: Grep import count
    IF import_count == 1 → advisory "[Single consumer, locality correct]"
    IF import_count <= 3 with different API contracts → advisory "[API contract isolation]"

Downgraded findings → "Advisory Findings" section in report.
Recalculate category scores excluding advisory findings from penalty.

Exempt: Security (ln-621), N+1 queries, CRITICAL build errors, concurrency (ln-628).

Output Format

MANDATORY READ: Load shared/templates/codebase_audit_template.md for full report structure.

Report is written to docs/project/codebase_audit.md using the template. Key sections:

  • Executive Summary, Compliance Score (9 categories), Severity Summary
  • Domain Health Summary + Cross-Domain Issues (if domain-aware)
  • Strengths, Findings by Category (global + domain-grouped), Recommended Actions
  • Sources Consulted

Phase 7: Write Report

MANDATORY READ: Load shared/templates/codebase_audit_template.md for report format.

Write consolidated report to docs/project/codebase_audit.md:

  • Use template structure from codebase_audit_template.md
  • Fill all sections with aggregated worker data
  • Include "Advisory Findings" section with context-validated downgrades
  • Overwrite previous report (each audit is a full snapshot)

Critical Rules

  • Worker applicability: Skip inapplicable workers based on project type (Phase 2); skipped workers get "N/A" score
  • Two-stage delegation: Global workers + Domain-aware workers (2 × N domains)
  • Domain discovery: Auto-detect domains from folder structure; fallback to global mode
  • Parallel execution: All applicable workers (global + domain-aware) run in PARALLEL
  • Single context gathering: Research best practices ONCE, pass contextStore to all workers
  • Metadata-only loading: Coordinator loads metadata only; workers load full file contents
  • Domain-grouped output: Architecture & Code Quality findings grouped by domain
  • File output only: Write results to codebase_audit.md, no task/story creation
  • Do not audit: Coordinator orchestrates only; audit logic lives in workers

Definition of Done

  • Project type detected; worker applicability determined; inapplicable workers documented with reason
  • Best practices researched via MCP tools for major dependencies
  • Domain discovery completed (domain_mode determined)
  • contextStore built with tech stack + best practices + domain info + output_dir
  • docs/project/.audit/ln-620/{YYYY-MM-DD}/ directory created (no deletion of previous runs)
  • Applicable global workers invoked in PARALLEL; each wrote report to {output_dir}/
  • Domain-aware workers (2 × N domains) invoked in PARALLEL; each wrote report to {output_dir}/
  • All workers completed successfully (or reported errors); return values parsed for scores/counts
  • Worker report files verified via Glob (expected count matches actual)
  • Results aggregated from return values (scores) + file reads (findings tables)
  • Domain Health Summary built (if domain_mode="domain-aware")
  • Cross-Domain DRY analysis completed from ln-623 FINDINGS-EXTENDED blocks (if domain-aware)
  • Context validation (Step 6.7) applied: ADR matches, cohesion checks, locality, trivial DRY filtered
  • Advisory findings separated from penalty-scored findings
  • Compliance score (X/10) calculated per category + overall (skipped workers + advisory excluded)
  • Executive Summary and Strengths sections included
  • Report written to docs/project/codebase_audit.md with Advisory Findings section
  • Sources consulted listed with URLs

Workers

See individual worker SKILL.md files for detailed audit rules:

Reference Files

  • Orchestrator lifecycle: shared/references/orchestrator_pattern.md
  • Task delegation pattern: shared/references/task_delegation_pattern.md
  • Audit scoring formula: shared/references/audit_scoring.md
  • Audit output schema: shared/references/audit_output_schema.md
  • Worker report template: shared/templates/audit_worker_report_template.md
  • Final report template: shared/templates/codebase_audit_template.md
  • Principles: docs/principles.md
  • Tech stack: docs/project/tech_stack.md
  • Kanban board: docs/tasks/kanban_board.md

Version: 5.0.0 Last Updated: 2025-12-23

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1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/codebase-auditor-l2-coordinator-mmbizjoy/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/codebase-auditor-l2-coordinator-mmbizjoy' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/codebase-auditor-l2-coordinator-mmbizjoy/download' --output '.skill-downloads/codebase-auditor-l2-coordinator-mmbizjoy/SKILL.md.part' && mv '.skill-downloads/codebase-auditor-l2-coordinator-mmbizjoy/SKILL.md.part' '.skill-downloads/codebase-auditor-l2-coordinator-mmbizjoy/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

Tools declared by the author (check availability in your agent): Read, Grep, Glob, Bash, WebFetch, WebSearch, mcp__Ref, mcp__context7, Skill

No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/codebase-auditor-l2-coordinator-mmbizjoy/SKILL.md' && test -s '.skill-downloads/codebase-auditor-l2-coordinator-mmbizjoy/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/ln-620-codebase-auditor' && cp -R '.skill-downloads/codebase-auditor-l2-coordinator-mmbizjoy' '.claude/skills/ln-620-codebase-auditor'

OpenSkills

OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.

Official OpenSkills installation
openskills install './.skill-downloads/codebase-auditor-l2-coordinator-mmbizjoy'

openskills read 'codebase-auditor-l2-coordinator-mmbizjoy'

Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.

For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

openskills sync

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/codebase-auditor-l2-coordinator-mmbizjoy/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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