github-bootstrap

Resolve GitHub PR review comments safely, read unresolved comments, validate each issue, make minimal fixes, test, commit, and resolve.

Use zero-install context minimization first, with optional local optimization tooling when available.

Accessibility review for semantic HTML, ARIA, keyboard support, focus, screen readers, contrast, and WCAG-oriented issues.

API and contract review for OpenAPI/AsyncAPI/protobuf changes, backwards compatibility, schemas, status codes, and examples.

Architecture review for SOLID, layering, boundaries, coupling, cohesion, extensibility, and maintainability.

Backend review for handlers, services, validation, errors, transactions, dependency boundaries, and service contracts.

Breaking-change review for public APIs, events, configs, feature flags, CLI behavior, and migration compatibility.

CI/CD review for workflows, artifact safety, caching, deployment gates, secrets, permissions, and reproducibility.

Compatibility review for backwards/forwards compatibility across APIs, events, database, config, clients, and deployment versions.

Compliance review for auditability, GDPR/PII, retention, financial controls, consent, and regulatory traceability.

Data review for migrations, data compatibility, transactions, indexing, retention, and data-loss risk.

Database review for queries, indexes, locks, migrations, isolation levels, query plans, and schema evolution.

Dependency and supply-chain review for package changes, vulnerabilities, licenses, pinning, and transitive risk.

Documentation and content review for README, changelog, comments, user-facing text, naming, and migration notes.

Map changed files to technical domain categories for routing to the correct specialist reviewers.

Defines the compact JSONL finding schema used by all PR specialist agents and the review auditor.

Merge duplicate specialist findings, resolve conflicts, and create a short final PR review summary.

Frontend review for React/TypeScript patterns, state management, rendering, bundle impact, forms, and UX regressions.

Infrastructure review for Terraform, Kubernetes, Helm, IAM, network policy, secrets, and runtime configuration.

Logic review for correctness, edge cases, state transitions, error handling, concurrency, and business invariants.

Review whether a patch fixes only the intended issue with minimal blast radius and no unrelated changes.

Observability review for logs, metrics, tracing, correlation IDs, error context, dashboards, and alertability.

Performance review for expensive loops, N+1 calls, memory pressure, latency, caching, and unnecessary IO.

Collect minimal PR context needed by orchestrators and specialists without reading full files or the whole repo.

Analyze pull request diffs efficiently and route files to the right review specialists without loading the whole repository.

Optimizes user prompts before implementation. Use when the user asks to improve, prepare, validate, reduce ambiguity, minimize token usage, or avoid iteration loops before sending a task to an AI coding agent.

Regression-risk review for behavior changes likely to break existing users, flows, integrations, or production data.

Resilience review for timeouts, retries, idempotency, circuit breakers, fallbacks, and failure isolation.

Classify PR risk and select which specialist reviewers should run based on changed files, diff shape, and risk hints.

Security review for auth, authorization, secrets, injection, crypto, dependency misuse, and unsafe data exposure.

Classify review findings into blocking, non-blocking, or note with consistent merge-risk rules.

Select the minimal useful tests to run based on changed files, impacted components, and repository conventions.

Test review for missing coverage, weak assertions, flaky tests, isolation, fixtures, and regression risk.

Requirements-to-implementation workflow. Use this when connecting requirements to design, implementation, testing, and delivery.

Integration and E2E testing design. Use this when writing integration tests, E2E tests, or deciding what belongs in each test layer.

Test implementation patterns. Use this when writing tests — table-driven tests, mocking, fixtures, assertions, and parallel execution.

Testing philosophy and strategy. Use this when deciding what to test, naming tests, or identifying corner cases.