name: principal-audit-refactor
description: Audit a local software project, produce a severity-ranked engineering review, and execute an approval-gated refactor plan. Use when Codex needs to assess prototype-quality or inconsistent codebases, run stack-aware checks, write timestamped audit artifacts, and then implement production-grade improvements with explicit safety boundaries, report contracts, and refactoring discipline.
metadata:
author: jovd83
version: 1.3.0
dispatcher-layer: execution
dispatcher-lifecycle: active
dispatcher-output-artifacts: audit_report, refactor_plan, refactor_summary
dispatcher-risk: high
dispatcher-writes-files: true
dispatcher-input-artifacts: repository_context, audit_scope, codebase_metrics, approval_state
dispatcher-capabilities: code-audit, refactor-planning, approval-gated-refactor
dispatcher-stack-tags: analysis, refactor, engineering-review
dispatcher-accepted-intents: audit_codebase, plan_refactor, execute_approved_refactor
dispatcher-category: analysis
Telemetry & Logging
[!IMPORTANT] All usage of this skill must be logged via the Skill Dispatcher to ensure audit logs and wallboard analytics are accurate: ./log-dispatch.cmd --skill <skill_name> --intent <intent> --model <model_name> --reason <reason> (or ./log-dispatch.sh on Linux)
Principal Audit & Refactor
Author: jovd83 | Version: 1.3.0
Use this skill to turn an unstable or inconsistent repository into a better-structured, safer, more maintainable codebase without collapsing discovery, audit, and mutation into one uncontrolled pass.
Operating Model
Work in two explicit modes:
- Audit mode: inspect the target project, run safe deterministic checks, and write an audit report.
- Refactor mode: only begin after the user explicitly approves the audit findings.
Keep the workflow grounded in the target repository, not the skill repository. Write generated reports into the target project's Technical_Reviews/ directory.
Safety Gates
Enforce these gates before mutating code:
- Confirm the target path the user wants audited. Default to the current working directory only when the intent is unambiguous.
- Detect whether the target is inside a git repository. If it is, inspect status before editing. If it is not, continue but explicitly note the lack of version-control safety.
- Do not require a perfectly clean tree to perform an audit. For refactoring, pause if unrelated changes create a real risk of overwriting user work.
- Never invent linter commands. Prefer project-native commands discovered from manifests, scripts, or tool configs. If no reliable deterministic check is available, say so and continue with manual review.
- Stop after writing the audit report and ask for approval. Do not begin implementation in the same phase unless the user has already authorized both audit and refactor work.
- Scope edits to the agreed target. Do not "boil the ocean" unless the user asked for a full-repository pass.
Workflow
1. Establish Scope
- Identify the target repository or subpath.
- Determine whether the user wants an audit only or audit plus refactor.
- Treat audit plus refactor as a two-step workflow with a hard approval gate between them.
2. Discover the Environment
- Inspect manifests and build files such as
package.json, pyproject.toml, Cargo.toml, go.mod, pom.xml, build.gradle, .csproj, Dockerfile, and CI configs. - Identify the main languages, frameworks, runtime, package manager, test stack, data layer, and entry points.
- Identify likely high-risk areas: core orchestration, auth, persistence, state management, heavy utility modules, or files already producing warnings.
- Prefer deterministic tooling when available: lint, typecheck, unit tests, static analysis, or build validation.
Read references/rubric.md once discovery is complete.
3. Produce the Audit
- Use references/report-contract.md and assets/audit-report-template.md.
- Write a timestamped audit file in
Technical_Reviews/ at the target project root. - Include concrete file paths, severity, risk, and recommended action.
- Base severity on evidence from code inspection and any deterministic tool output you were able to run.
- If evidence is incomplete, state the limitation rather than over-claiming.
4. Pause for Approval
After saving the audit report:
- summarize the top risks,
- name the report path, and
- ask for explicit approval before editing code.
5. Execute the Refactor
Only after approval:
- Read references/refactor-execution.md.
- Refactor by file or bounded subsystem, not by isolated smell.
- Prefer in-place repository edits over chat-only "full file output" unless the user explicitly asks for copy-paste output.
- Preserve behavior unless the audit explicitly calls for a behavioral fix.
- Add or update tests when the repository already has a testing story and the change materially benefits from coverage.
- Write a timestamped execution summary using assets/refactor-report-template.md.
Output Contracts
Audit report
Must include:
- project name or scoped target,
- timestamp,
- detected stack,
- deterministic checks run and their outcomes,
- prioritized findings with severity,
- maintainability score with a clear scoring rule,
- recommended refactor sequence,
- explicit open questions or blocked areas.
Refactor report
Must include:
- audit report reference,
- files changed,
- resolved findings,
- follow-up work intentionally left out of scope,
- validation performed after edits.
Memory Model
Use memory deliberately:
- Runtime memory: current findings, tool output, and the active refactor plan for this run only.
- Project-local memory: persisted audit and refactor reports written into
Technical_Reviews/ in the target repository. - Shared memory: out of scope for this skill. If cross-project reuse is needed, integrate with a separate shared-memory skill instead of storing shared memory here.
Do not automatically promote runtime observations into persistent artifacts unless they are useful to the user or needed for traceability.
Failure Handling
If the workflow becomes unreliable, degrade gracefully:
- Missing repo metadata: continue with manual discovery and note the limitation.
- Missing or broken tooling: capture the failure, avoid guessing commands, continue with review.
- Large or tangled files: split work into bounded extractions before deeper cleanup.
- Unsafe ambiguity about intent or target path: pause and confirm before editing.
- Conflicts with user changes: stop and ask before overwriting.
Gotchas
Watch out for these common friction points:
- Root Ambiguity: In monorepos, the skill might default to the root. Always clarify if the audit should be scoped to a specific package or directory.
- Context Window Limits: For very large repositories or files, the agent may not see the full context in a single pass. Consider splitting large audits into subsystems.
- Generated Artifacts: Ensure you are auditing source code and not generated files (e.g.,
dist/, build/, node_modules/). - Tooling Hallucination: If native test/lint scripts are missing, strictly report the gap rather than inventing commands to simulate a "deterministic" check.
- State Drift: If the user makes manual edits after an audit but before a refactor, the audit results may become stale. Briefly re-verify critical files before mutating.
Resource Map