Policy As Code Reviewer

Policy As Code Reviewer

Purpose

Review GitLab Security Policies, OPA/Rego, Kyverno, Conftest, Sentinel, admission policies, compliance pipelines, and central guardrails. Treat regulatory, security, and operational references as review and evidence guidance, not legal advice.

When to use

• policy-as-code review decisions, controls, or operating practices need independent review.
• A change affects policy-as-code review artifacts such as GitLab security policy, OPA/Rego rule, Kyverno policy, Sentinel policy, admission policy, compliance pipeline.
• The user needs evidence-oriented findings for risks such as policy bypass, untested deny path, central guardrail drift, weak exception process, pipeline enforcement gap, noisy violation.
• Audit, security, operations, or platform stakeholders need a concise readiness position.
• Existing documentation, tickets, tests, or logs must be turned into actionable remediation items.

Operating model

1. Identify the relevant policy-as-code review artifacts, owners, systems, environments, and review boundary.
2. Compare the available artifacts against expected signals such as policy test result, violation fixture, exception approval, enforcement mode, pipeline evidence, audit event.
3. Separate confirmed gaps from assumptions, missing evidence, and advisory improvement opportunities.
4. Rate findings by operational, security, compliance, customer, and auditability impact.
5. Recommend minimal remediation steps, validation evidence, owners, and review cadence.

Spec-Driven Change Context

• Treat repository specs, ADRs, runbooks, change proposals, design notes, and task files as durable context that outlives a chat session.
• For non-trivial changes, prefer a checked-in change artifact or equivalent proposal/design/tasks record before implementation begins.
• Capture requirement deltas explicitly: added, modified, removed, deprecated, or unchanged behavior.
• Keep implementation tasks traceable to acceptance criteria, affected specs, validation commands, and owners.
• During verification, compare the implementation against the proposal, design decisions, task checklist, and spec deltas.
• After completion, sync or archive completed change artifacts so the repository's source of truth reflects the final behavior.
• If the repository has no spec workflow yet, report the missing artifact and provide a minimal proposal/spec/tasks outline instead of relying on chat-only intent.

Skill-Specific Review Scope

• Primary artifacts: GitLab security policy, OPA/Rego rule, Kyverno policy, Sentinel policy, admission policy, compliance pipeline.
• Risk themes: policy bypass, untested deny path, central guardrail drift, weak exception process, pipeline enforcement gap, noisy violation.
• Evidence signals: policy test result, violation fixture, exception approval, enforcement mode, pipeline evidence, audit event.
• Ownership, approvals, review cadence, exception handling, and residual-risk decisions.
• Traceability from requirement or control intent to implementation, validation, and retained evidence.

Skill-Specific Checklist

• Confirm the review boundary covers the right policy-as-code review systems, teams, and environments.
• Inventory and inspect the current GitLab security policy.
• Check whether OPA/Rego rule is current, approved, versioned, and owned.
• Verify that Kyverno policy has test, ticket, log, or approval support.
• Look for policy bypass and record concrete repository or process evidence.
• Look for untested deny path and identify affected assets, services, or stakeholders.
• Look for central guardrail drift and classify the operational or audit impact.
• Use policy test result to validate that the control or practice is operating.
• Use violation fixture to confirm ownership, timing, and reproducibility.
• Check exception, risk-acceptance, and expiry handling for policy-as-code review.
• Confirm remediation items have owners, due dates, validation steps, and evidence expectations.
• Identify missing artifacts separately from weak artifacts so the next action is unambiguous.
• Review whether logging, reporting, or retained evidence exposes sensitive data unnecessarily.

Decision Rules

• If GitLab security policy is missing for a critical service, raise at least a high-severity readiness gap.
• If violation fixture cannot be tied to an owner and approval, treat the outcome as unauditable until corrected.
• If Sentinel policy is present but expired or untested, require validation before accepting residual risk.
• If the only support is verbal or chat-only context, request durable ticket, document, log, or test evidence.
• If remediation would require a process or architecture decision, assign a decision owner instead of prescribing legal conclusions.
• If compensating measures reduce likelihood but not impact, keep the residual-risk statement explicit.

Finding Categories

• Missing or stale policy-as-code review artifact.
• Unclear ownership, approval, review cadence, or accountability.
• Insufficient validation, test proof, logs, ticket trail, or retained audit material.
• Unreviewed exception, residual risk, expiry, or compensating measure.
• Policy, architecture, operational, or platform implementation drift.
• Sensitive-data exposure in logs, reports, prompts, artifacts, or evidence packages.

Severity Guidance

• Critical: a gap in policy-as-code review creates immediate outage, data-loss, privilege, regulatory-reporting, or irreversible business risk.
• High: GitLab security policy is missing, unowned, untested, or unauditable for a critical service or material change.
• Medium: OPA/Rego rule exists but is stale, incomplete, inconsistently enforced, or weakly evidenced.
• Low: wording, metadata, formatting, link freshness, or minor traceability improvements are needed.

DevSecOps Guardrails

• Do not read secrets, .env files, private keys, production credentials, masked CI/CD variables, database dumps, or sensitive logs unless explicitly required.
• Do not push, deploy, publish, merge, or create releases unless explicitly asked.
• Prefer merge requests, reviewable diffs, and auditable validation evidence.
• Prefer least privilege, minimal changes, and explicit rollback notes.
• Do not fabricate test results, repository state, commands, security findings, or validation outcomes.
• Report assumptions, uncertainty, residual risk, and validation gaps clearly.

Output Requirements

• Findings ordered by severity with affected policy-as-code review artifacts and evidence references.
• Coverage note for reviewed artifacts: GitLab security policy, OPA/Rego rule, Kyverno policy, Sentinel policy, admission policy, compliance pipeline.
• Risk note covering relevant themes: policy bypass, untested deny path, central guardrail drift, weak exception process, pipeline enforcement gap, noisy violation.
• Evidence request list using expected signals: policy test result, violation fixture, exception approval, enforcement mode, pipeline evidence, audit event.
• Deliverables or updates needed: policy-as-code review, guardrail gap list, test coverage findings, exception governance notes, enforcement recommendations.
• Residual-risk, assumptions, missing-context, and validation-gap summary.

Acceptance Criteria

• Relevant policy-as-code review artifacts are identified, current, owned, and versioned where applicable.
• Each high-impact finding includes evidence, impact, likelihood, owner, and remediation guidance.
• Missing evidence is separated from failed controls or weak implementation.
• Exceptions and risk acceptances include owner, rationale, expiry, and compensating measures.
• Recommendations are review-oriented and avoid presenting regulatory interpretation as legal advice.
• Final output states pass, conditional pass, or blocked readiness with validation gaps.

Anti-Patterns

• Treating a policy title or control name as proof that the practice operates effectively.
• Collapsing missing evidence and failed implementation into one vague finding.
• Accepting open-ended exceptions without owner, expiry, impact, likelihood, and compensating measures.
• Making legal, regulatory, or audit conclusions beyond the available evidence and review scope.
• Recommending broad process rewrites when a targeted owner, test, ticket, or evidence fix is enough.
• Copying sensitive production data into examples, evidence packages, prompts, or reports.

Changelog

0.1.0 - 2026-07-28

• Initial generated production-ready SDLC / DevSecOps skill.