📄 CodeRabbit inference engine (.agents/metrics/baseline-report.md)

Infrastructure files (including .githooks/pre-commit) must receive security review before deployment

Files:

• .github/scripts/AIReviewCommon.Tests.ps1
• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml
• .github/scripts/AIReviewCommon.psm1
• .github/prompts/pr-quality-gate-qa.md

📄 CodeRabbit inference engine (.agents/architecture/ADR-006-thin-workflows-testable-modules.md)

Create Pester tests (.Tests.ps1) for all PowerShell modules with 80% coverage for all exported functions

Files:

• .github/scripts/AIReviewCommon.Tests.ps1

📄 CodeRabbit inference engine (.agents/critique/003-pr-60-remediation-plan-critique.md)

.github/**/*.ps1: All AI output must be validated before shell use - reject labels/milestones with dangerous characters: newlines, backticks, shell metacharacters (|, &, <, >, ;, $, etc.)
Use security-hardened regex pattern for label validation: '^[a-zA-Z0-9](?:[a-zA-Z0-9 _-.]{0,48}[a-zA-Z0-9])?$|^[a-zA-Z0-9]$' with explicit length limit (1-50 characters) and blocklist check for dangerous characters before pattern matching
Validate all file paths using Assert-ValidBodyFile with appropriate AllowedBase parameter set to restrict traversal attacks: use $env:RUNNER_TEMP for GitHub Actions temp files, repo root for checked-in files, current directory for user-provided paths
Implement defense-in-depth validation: check for dangerous characters blocklist BEFORE pattern matching, then validate against strict ASCII-only regex, then verify length constraints (1-50 characters for labels)

PowerShell scripts in workflows must pass PSScriptAnalyzer linting checks

Validate label format with regex ^[\w-.\s]+$ and enforce 50-character limit before applying labels via gh CLI

Before ANY GitHub operation, check .claude/skills/github/ directory for existing capability

Files:

• .github/scripts/AIReviewCommon.Tests.ps1

📄 CodeRabbit inference engine (.agents/critique/003-pr-60-remediation-plan-critique.md)

.github/**/*.Tests.ps1: Phase 1 task acceptance criteria must include test execution verification: Run Pester tests for each modified function and confirm ALL tests PASS before marking task complete
Create comprehensive test suites before Phase 1 implementation with explicit test categories: injection attack tests (5+), exit code tests (4+), error aggregation tests (3+), and context detection tests (4+)

Files:

• .github/scripts/AIReviewCommon.Tests.ps1

📄 CodeRabbit inference engine (.agents/planning/PR-60/003-pr-60-plan-critique.md)

.github/scripts/**/*.ps1: Add test verification to Phase 1 remediation tasks including running existing tests with Invoke-Pester -Path '.github/scripts', adding smoke tests for new behavior, and manual verification in workflow runs
Function docstrings must explain context-dependent behavior, particularly for functions that change behavior based on execution context like Write-ErrorAndExit
PowerShell script modifications should prefer converting only specific logic components (e.g., label parsing) in Phase 1 rather than full workflow conversion to minimize scope and reduce risk
Security-critical functions like command injection prevention and error handling must have 100% test coverage before production merge

Files:

• .github/scripts/AIReviewCommon.Tests.ps1

📄 CodeRabbit inference engine (.agents/planning/pr-60-qa-review.md)

.github/scripts/AIReviewCommon.Tests.ps1: Maintain PowerShell test coverage at 100%+ for AIReviewCommon.psm1 module using Pester framework - verify function coverage metrics > implementation LOC
Test label parsing edge cases: empty/null/whitespace input, adjacent labels without spaces, XSS in collapsible sections, unparseable output
Test verdict aggregation with empty verdict arrays, multiple verdict sources, priority handling (CRITICAL_FAIL > WARN > PASS), and fallback to CRITICAL_FAIL on aggregation failure
Use Pester mocking framework in PowerShell tests to mock external dependencies (Start-Sleep for backoff timing, gh CLI calls) and use TestDrive for isolated file system operations

Files:

• .github/scripts/AIReviewCommon.Tests.ps1

📄 CodeRabbit inference engine (.agents/retrospective/2025-12-18-ai-workflow-implementation.md)

AI automation in CI/CD requires verdict tokens (PASS/WARN/CRITICAL_FAIL) for deterministic bash parsing without AI interpretation

Files:

• .github/scripts/AIReviewCommon.Tests.ps1
• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml
• .github/scripts/AIReviewCommon.psm1
• .github/prompts/pr-quality-gate-qa.md

📄 CodeRabbit inference engine (.agents/sessions/2025-12-18-session-33-pr-60-merge-readiness.md)

{.github/scripts/**/*.ps1,.claude/skills/**/*.ps1}: PowerShell-only implementation for agent scripts (no bash, Python, or external dependencies)
Document all security vulnerability fixes with blocking injection vectors in code comments

Files:

• .github/scripts/AIReviewCommon.Tests.ps1

📄 CodeRabbit inference engine (.agents/governance/interviews/security-interview.md)

Review infrastructure code changes including GitHub Actions workflows, git hooks, and Dockerfile for security vulnerabilities

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/metrics/dashboard-template.md)

Ensure infrastructure files in GitHub workflows directory are reviewed by agents with target rate of 100%

Implement full CodeRabbit enforcement for CI/CD workflow files in .github/workflows/ directory

.github/workflows/*: Detect files matching .github/workflows/* as infrastructure changes requiring specialist review from devops and security agents
GitHub Actions workflows must include an explicit permissions block with minimally privileged permissions
GitHub Actions workflows must not use pull_request_target trigger with actions/checkout action using pull request head SHA reference, as this creates a dangerous security pattern
GitHub Actions workflows requiring test reporting must explicitly grant checks: write permission for dorny/test-reporter compatibility
GitHub Actions workflows must avoid using overly permissive permissions: write-all and instead use explicit minimal permissions

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/security/infrastructure-file-patterns.md)

GitHub Actions workflow files (.github/workflows/*.yml and .github/workflows/*.yaml) should trigger security agent review due to critical security implications

Add security detection check to CI/CD pipelines to analyze staged files for infrastructure changes before implementation

.github/workflows/*.{yml,yaml}: Infrastructure files (.github/workflows/) require devops and security agent review before commit
Add pre-commit validation that fails on infrastructure files (.github/workflows/) lacking security review documentation
Infrastructure files must include a security impact analysis document before creation or modification
Retroactive security review is required for quick-fix changes to workflow files made without pre-commit review
Workflow files must validate that all required permissions are explicitly declared and justified

Keep workflow YAML files light and thin - MUST NOT put complex logic in workflow YAML files; use thin workflows with calls to external testable modules or skills

GitHub Actions workflows should remain thin and delegate complex logic to PowerShell modules rather than embedding bash-like commands in workflow YAML run blocks

.github/workflows/*.{yml,yaml}: Never use || true pattern without explicit error handling and ADR justification
Do not use || true error suppression in workflows without documenting rationale in an ADR

Use thin workflow pattern: minimize logic in YAML files, delegate complex operations to PowerShell modules

.github/workflows/*.{yml,yaml}: Use YAML heredoc with proper indentation for multi-line GitHub Actions values
Use GH_TOKEN for auto-authentication in GitHub Actions shell scripts
Use fixed-length lookbehinds for regex patterns in GitHub Actions
GitHub Actions outputs must be single-line format
Matrix jobs in GitHub Actions should use artifacts for output storage
Use environment variables for shell command interpolation in GitHub Actions to prevent injection vulnerabilities
Use verdict tokens for str...

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/utilities/security-detection/SKILL.md)

CI/CD workflow files (.github/workflows/*), git hooks (.githooks/*, .husky/*), and authentication code (**/Auth/**, **/Security/**) require security agent review (CRITICAL level)

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/analysis/pr41-issue-analysis.md)

.github/workflows/*.yml: Use dotnet-nunit reporter in dorny/test-reporter@v1 when Pester tests output NUnitXml format
Add explicit permissions block to GitHub Actions workflow jobs, specifying minimal required permissions (e.g., contents: read and checks: write for test reporting workflows)

.github/workflows/*.yml: Use minimal GitHub Actions permissions in CI workflows
Add workflow_dispatch trigger to GitHub Actions workflows for manual triggering capability
Add PowerShell-Yaml module installation step in CI workflows
Use ubuntu-latest for drift detection CI workflows for lighter weight execution
Add issue deduplication for drift alerts in GitHub Actions workflows
Use path filtering appropriately scoped in GitHub Actions workflows

CI/CD pipeline must include a drift-linting job that compares Claude agent content against generated VS Code and Copilot CLI variants on every PR modifying agent files

Create automated CI validation to detect absolute paths (Windows, macOS, Linux patterns) in markdown files with colored output, line numbers, and remediation steps

Configure concurrency groups in GitHub Actions workflows to prevent comment spam and race conditions when multiple commits trigger parallel workflow runs on the same PR

.github/workflows/*.yml: Remove silent || true error suppression from critical operations; instead track failures in arrays and provide summarized error reporting at workflow completion
Use minimal token scopes in GitHub Actions workflows: use repo scope for read-only operations, issues:write for issue modifications, and workflow permissions declarations following principle of least privilege

.github/workflows/*.yml: Store heredoc content in separate files instead of inline within YAML run: blocks to avoid YAML parsing errors when content lacks proper indentation
Use github.token (workflow's built-in token) for PR comments in GitHub Actions instead of service account PATs, as it automatically has write access t...

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/planning/prd-pre-pr-security-gate.md)

Detect files matching .github/**/*.yml as infrastructure changes requiring specialist review from devops and security agents

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/retrospective/pr-feedback-remediation.md)

Use 'ubuntu-latest' for CI runner preference instead of 'windows-latest' for significantly faster performance, except for PowerShell Desktop or Windows-specific features

.github/workflows/**/*.{yml,yaml}: Workflows should be thin and contain only orchestration logic; all business logic (parsing, validation, formatting) must be extracted to PowerShell modules (.psm1)
Keep workflow YAML files to a maximum of 100 lines (orchestration only)
Do not parse complex strings (verdict, labels, etc.) in workflow YAML run: blocks; delegate to PowerShell modules
Do not validate business rules directly in workflow YAML; delegate to PowerShell modules
All PowerShell scripting for workflows must be PowerShell-only (no bash or other shell languages embedded in workflows)

.github/workflows/**/*.{yml,yaml}: PowerShell used consistently for label and milestone parsing in AI workflow (extract parsing logic to AIReviewCommon.psm1::Get-LabelsFromAIOutput rather than inline bash)
Use ::error:: GitHub Actions format for error output instead of echo or Write-Error to ensure errors are properly captured and cause workflow failure
Remove all '|| true' patterns and silent failure suppression in workflow steps - errors must be aggregated and reported explicitly using ::error:: format
Add token masking with ::add-mask:: before using secrets in workflow run steps to prevent accidental token leakage in logs
Replace secrets.BOT_PAT with github.token for issue and PR operations to minimize token privileges and reduce security attack surface
Document minimum required token scopes in workflow comments for each operation (e.g., 'repo' scope for issue edit and label application, 'read' scope for readonly operations)
Extract AI workflow parsing logic to testable PowerShell module functions (AIReviewCommon.psm1) rather than inline bash - enables unit testing in isolation and reduces regression risk

.github/workflows/**/*.{yml,yaml}: Use bash/PowerShell error collection pattern: initialize FAILED_...

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/skills/ci-runner-preference.md)

**/.github/workflows/*.{yml,yaml}: Use ubuntu-latest (or linux-latest) runners for GitHub Actions workflows instead of windows-latest for better CI/CD pipeline performance
Only use windows-latest runner when PowerShell Desktop (5.1) is required, Windows-specific features are needed, or testing Windows-only scenarios
Prefer PowerShell Core (pwsh) over PowerShell Desktop for GitHub Actions scripts to enable cross-platform compatibility on Linux runners

Workflows SHOULD be less than 100 lines, containing orchestration only. Business logic SHOULD be extracted to PowerShell modules (.psm1).

PowerShell workflow files must follow the thin-workflow pattern where orchestration logic stays in the workflow and business logic is extracted to reusable modules

Maintain consistent token scopes and authentication strategy throughout workflows; use the same token source for all related operations to avoid permission errors

**/.github/workflows/*.{yml,yaml}: Avoid code injection vulnerabilities by never directly interpolating unsanitized GitHub context variables (like ${{ github.event.issue.title }} or ${{ github.event.issue.body }}) into bash commands; instead save them to files using heredoc syntax and read them back
Use toJSON() to escape GitHub context variables when passing them to bash commands, or employ input validation before using variables in shell contexts
GitHub Actions workflows should request only the minimum necessary permissions (principle of least privilege) required for their operations

**/.github/workflows/*.{yml,yaml}: When ≥2 GitHub Actions workflows share logic, extract to composite action with parameterized inputs for reusability
GitHub Actions workflow files should include YAML syntax validation and actionlint checks in pre-commit configuration

**/.github/workflows/*.{yml,yaml}: Use artifacts instead of job outputs for passing data between matrix jobs in GitHub Actions workflows
Use environment variables for shell variable expans...

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/steering/security-practices.md)

Implement OWASP Top 10 prevention practices in GitHub Actions workflows

Use secure defaults and minimal exposure for security misconfiguration prevention

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

⚙️ CodeRabbit configuration file

.github/workflows/**: SECURITY-CRITICAL PATH - ASSERTIVE ENFORCEMENT
Review for: - Authentication and authorization (secrets handling, OIDC) - Credential exposure (env vars, git output, logs) - Injection vulnerabilities (command injection, script injection) - Race conditions (concurrent jobs, artifact operations) - Resource exhaustion (limits on runners, matrix expansions)
Flag: - Unquoted variables in shell commands - Direct use of user input in scripts - Missing error handling and early exit conditions - Hardcoded secrets or credentials - Unsafe use of 3rd party actions
DO NOT IGNORE any security-related findings on this path.

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/architecture/DESIGN-REVIEW-pr-60-remediation-architecture.md)

Use GitHub Actions workflow steps with PowerShell for JSON parsing and data manipulation; reserve bash only for simple npm install, git operations, and environment variable exports

Aggregate errors across workflow steps using error accumulation arrays and export failure summary via GITHUB_OUTPUT

.github/workflows/**/*.yml: GitHub Actions workflows orchestrating multiple agents should use matrix strategy with fail-fast: false to ensure all reviews complete
Use artifact passing (not job outputs) to transfer data between workflow jobs when using matrix strategy
Implement idempotency in workflow comment generation using comment markers to distinguish update vs create operations
Use skip optimization to check for docs-only changes before executing expensive AI review jobs
Add CI validation step to verify prompt templates include required output format markers before merging

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/governance/PROJECT-CONSTRAINTS.md)

**/.github/workflows/**/*.{yml,yaml}: MUST NOT put business logic in workflow YAML files
SHOULD keep workflows under 100 lines (orchestration only)

Workflows must be thin and composed of testable, reusable modules

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/planning/PR-60/001-pr-60-review-gap-analysis.md)

Use unique identifiers (e.g., run ID, timestamp) for temporary file paths in CI/CD workflows to prevent conflicts in concurrent runs on shared runners

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/planning/PR-60/004-pr-60-implementation-review.md)

**/.github/workflows/**/*.yml: Replace bash label parsing in GitHub Actions workflows with PowerShell validation to prevent command injection via untrusted AI output
Validate all label strings against regex pattern '^[\w-.\s]{1,50}$' before applying to GitHub issues
Validate all category strings against regex pattern '^[\w-]{1,30}$' before using in workflow outputs
Validate all milestone strings against regex pattern '^[\w-.\s]{1,50}$' before assigning to issues
Use explicit error handling with informative error messages instead of '|| true' for GitHub CLI (gh) commands that should not fail silently
Keep '|| true' only for commands where empty/missing results are valid expected outcomes (e.g., grep with no matches, find with no results)
Verify GitHub CLI authentication status is successful before attempting API operations in CI workflows
Log validation rejections with details (invalid format, rejected label) for debugging label application failures
Provide detailed error messages in GitHub Actions workflow steps including context (what failed, why, what to check)
Use PowerShell 'Write-Host' with color output for structured workflow logging instead of plain echo statements
Use '|| true' in workflows only for commands where missing data is an expected valid state; document the reason in comments
Validate workflow inputs and outputs against strict regex patterns before using them in GitHub API commands

**/.github/workflows/**/*.yml: Use environment variables instead of direct ${{ }} template syntax in shell scripts to prevent shell injection attacks
Use artifacts instead of job outputs to pass data between matrix job legs, since outputs only expose one matrix leg
Prepare multi-line content via prior steps with GITHUB_OUTPUT heredoc syntax rather than attempting to execute shell commands in YAML with: inputs

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/planning/PR-60/007-phase-1-detailed-schedule.md)

Use PowerShell-only code (no bash, Python, or shell scripts) with all workflow steps configured with 'shell: pwsh' per ADR-006

Use quoted heredoc (with 'EOF' delimiter) for safely handling github.event.pull_request.title and github.event.pull_request.body in bash env vars to prevent code injection

GitHub Actions workflows must use PowerShell functions from exported modules rather than inline bash parsing (grep/sed/tr) for consistent security and testability

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/planning/pr-60-focused-plan.md)

Use sed with POSIX character classes instead of grep -P for regex patterns to ensure portability across Linux and macOS (grep -P is GNU-only)

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/planning/pr-60-qa-review.md)

.github/workflows/ai-pr-quality-gate.yml: Run bash tests in CI pipeline BEFORE ai-pr-quality-gate runs - add workflow step with: 'bats .github/scripts/ai-review-common.Tests.sh' and fail PR if tests fail
Measure bash script test coverage using kcov or bashcov tool targeting ≥80% line coverage minimum for ai-review-common.sh

The AI PR Quality Gate workflow should run all 6 agents (security, qa, analyst, architect, devops, roadmap) in parallel and aggregate their verdicts

For PR quality gates, use adaptive context mode: full diff if <500 lines, summary for larger diffs

Files:

• .github/workflows/ai-pr-quality-gate.yml

📄 CodeRabbit inference engine (.agents/planning/pr-60-security-review.md)

.github/{workflows,scripts}/**/*.{yml,yaml,sh}: Avoid leaking sensitive information or internal configuration details in error messages and workflow logs that could be visible to attackers. Use generic error messages in production and reserve detailed diagnostics for debug logs only.
Sanitize and validate all untrusted user input (such as GitHub event data like PR titles, issue bodies, commit messages) before using in shell commands, API calls, or other operations that could interpret special characters.
When updating GitHub comments in workflows, use idempotent markers (HTML comments with unique identifiers) in comment bodies to enable safe updates by specific comment ID rather than relying on comment position.

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/sessions/2025-12-18-session-03-ai-workflow-implementation.md)

.github/workflows/ai-*.yml: Use structured verdict tokens (PASS, WARN, CRITICAL_FAIL) for AI agent outputs in GitHub Actions workflows to enable machine parsing for CI decisions
Implement sequential agent invocation in workflows to allow dependencies between analyses
Implement concurrency groups in GitHub Actions workflows to prevent duplicate reviews on rapid commits
Use hybrid reporting (PR comments + check annotations) for AI review verdicts in GitHub Actions

.github/workflows/ai-*.yml: Use GitHub markdown alert syntax (> [!TIP], > [!CAUTION]) for verdict blocks in AI workflow comments
Add emoji headers (🤖, 🔒, 🧪, 📊, 📋, 📐) for visual appeal in AI workflow PR comments
Include verdict badges (✅ PASS, ⚠️ WARN, ❌ FAIL) in summary tables of AI workflow comments
Use collapsible details sections for verbose content in AI workflow comments to reduce visual noise
Add HTML comment markers in AI workflow comments for idempotent comment updates
Include a Run Details footer with metadata table (run ID, trigger info) in AI workflow comments
Add branded footer with links to workflow file and repository in AI workflow comments
Use left-aligned text and center-aligned status icons in AI workflow comment tables

.github/workflows/ai-*.yml: Run AI agents in parallel matrix jobs with fail-fast: false to ensure all reviews complete
Include collapsible 'Walkthrough' sections in AI workflow PR comments explaining what each agent does

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/sessions/2025-12-18-session-03-ai-workflow-implementation.md)

Use adaptive context assembly in AI review workflows to handle large PRs gracefully (>500 lines)

Files:

• .github/workflows/ai-pr-quality-gate.yml

📄 CodeRabbit inference engine (.agents/sessions/2025-12-18-session-04-ai-workflow-debugging.md)

Avoid explicit gh auth login --with-token when GH_TOKEN environment variable is already set, as gh CLI automatically uses the env var and will fail with exit code 1

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/sessions/2025-12-18-session-13-workflow-lessons.md)

Use composite actions to encapsulate reusable workflow steps (Node.js/npm/Copilot CLI setup, authentication, agent loading, verdict parsing)

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/sessions/2025-12-18-session-13-workflow-lessons.md)

Use structured verdict tokens (PASS | WARN | CRITICAL_FAIL) for AI agent workflow automation decisions

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/sessions/2025-12-18-session-13-workflow-lessons.md)

Convert single-job loops to multi-job matrix structures (detect → validate → aggregate) for parallel validation with artifact passing

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/sessions/2025-12-18-session-34-pr-60-comment-response.md)

{.github/**/*.{sh,yml,yaml},**/*.sh}: Avoid gh auth login authentication patterns; use session-based authentication instead (reference Session 04 for implementation details)
Use secret masking for sensitive tokens like BOT_PAT in shell commands and CI/CD workflows

Files:

• .github/workflows/ai-pr-quality-gate.yml
• .github/workflows/ai-spec-validation.yml

📄 CodeRabbit inference engine (.agents/architecture/ADR-006-thin-workflows-testable-modules.md)

.github/scripts/**/*.psm1: PowerShell modules (.psm1) must contain ALL business logic and have comprehensive Pester tests with 80%+ code coverage
PowerShell module functions must use verb-noun naming format and export only public functions
PowerShell modules should not directly call GitHub CLI (gh) commands; use wrappers from .claude/skills/github/ instead
PowerShell modules should be pure functions where possible (input → output, no side effects)

Files:

• .github/scripts/AIReviewCommon.psm1

📄 CodeRabbit inference engine (.agents/security/PIV-PR60-Phase1.md)

.github/scripts/AIReviewCommon.psm1: Use hardened regex pattern ^[a-zA-Z0-9][a-zA-Z0-9 _\-\.]{0,48}[a-zA-Z0-9]?$ for command injection prevention in label validation to block injection vectors including semicolons, backticks, dollar-parens, pipes, and newlines
Implement fail-closed approach for label validation: invalid labels must be rejected with warnings rather than thrown exceptions, and rejection attempts must be logged for security monitoring

Files:

• .github/scripts/AIReviewCommon.psm1

📄 CodeRabbit inference engine (.agents/sessions/2025-12-18-session-34-pr-60-comment-response.md)

Bash scripts should be migrated to PowerShell (use PowerShell modules like AIReviewCommon.psm1 instead of bash scripts like ai-review-common.sh)

Files:

• .github/scripts/AIReviewCommon.psm1

📄 CodeRabbit inference engine (.agents/planning/pr-60-architect-review.md)

.github/prompts/**/*.md: Organize prompt templates in .github/prompts/ directory with naming convention: {workflow-name}-{agent-name}.md
Prompt templates should include structured output format instructions with VERDICT:, LABEL:, and MILESTONE: markers

Files:

• .github/prompts/pr-quality-gate-qa.md

📄 CodeRabbit inference engine (.agents/retrospective/2025-12-18-ai-workflow-implementation.md)

Use structured output format (PASS/WARN/CRITICAL_FAIL tokens) in GitHub Actions AI review prompts to enable deterministic bash parsing

Files:

• .github/prompts/pr-quality-gate-qa.md

📄 CodeRabbit inference engine (.agents/sessions/2025-12-18-session-03-ai-workflow-implementation.md)

Create prompt templates for each specialized AI agent use case in .github/prompts/ directory

Use structured verdict tokens (PASS, WARN, CRITICAL_FAIL) in AI agent output for deterministic bash parsing

Files:

• .github/prompts/pr-quality-gate-qa.md

📄 CodeRabbit inference engine (.agents/sessions/2025-12-18-session-11-expand-quality-gate.md)

.github/prompts/pr-quality-gate-*.md: Follow the same prompt structure as existing agents (focus areas, output requirements, verdict format) when creating new AI agent prompts
All AI agent prompts must use the same PASS/WARN/CRITICAL_FAIL verdict structure for consistency in verdict aggregation

Files:

• .github/prompts/pr-quality-gate-qa.md