Skill do Reviewer Final para validação completa antes do deploy. Use quando precisar validar que todos os passos do pipeline foram executados, checar qualidade de código, confirmar segurança, confirmar QA, confirmar documentação, ou gerar relatório de aprovação/rejeição. Trigger em: "review final", "reviewer", "aprovação", "rejeição", "validação final", "gate de deploy", "checklist final", "aprovar deploy", "pode deployar", "pronto pra produção", "validar entrega", "review completo", "última verificação".

Workflow 3: Full paper writing pipeline. Orchestrates paper-plan → paper-figure → figure-spec/paper-illustration/mermaid-diagram → paper-write → paper-compile → auto-paper-improvement-loop to go from a narrative report to a polished PDF. At `— effort: max | beast` (or explicit `— assurance: submission`), Phase 6 gates the Final Report on `tools/verify_paper_audits.sh`; the PDF is labelled `submission-ready` only when the external verifier is green. Use when user says "写论文全流程", "write paper pipeline", "从报告到PDF", "paper writing", or wants the complete paper generation workflow.

Run a comprehensive health check of the joelclaw system — k8s cluster, worker, Inngest, Redis, Qdrant, tests, TypeScript, repo sync, memory pipeline, pi-tools, git config, active loops, disk, stale tests. Outputs a 1-10 score with per-component breakdown. Use when: 'system health', 'health check', 'is everything working', 'system status', 'how's the system', 'check everything', or at session start to orient.

Query historical crypto market data from 0xArchive across Hyperliquid, Lighter.xyz, and HIP-3. Covers orderbooks, trades, candles, funding rates, open interest, liquidations, and data quality. Use when the user asks about crypto market data, orderbooks, trades, funding rates, or historical prices on Hyperliquid, Lighter.xyz, or HIP-3.

Enrich an IOC (IP, domain, hash, URL) with threat intelligence. Use when you need to look up reputation and context for an indicator using GTI and SIEM. Returns threat intel findings, SIEM entity summary, and IOC match status.

Orchestrate Xcode build optimization by benchmarking first, running the specialist analysis skills, prioritizing findings, requesting explicit approval, delegating approved fixes to xcode-build-fixer, and re-benchmarking after changes. Use when a developer wants an end-to-end build optimization workflow, asks to speed up Xcode builds, wants a full build audit, or needs a recommend-first optimization pass covering compilation, project settings, and packages.

Apply approved Xcode build optimization changes following best practices, then re-benchmark to verify improvement. Use when a developer has an approved optimization plan from xcode-build-orchestrator, wants to apply specific build fixes, needs help implementing build setting changes, script phase guards, source-level compilation fixes, or SPM restructuring that was recommended by an analysis skill.

Benchmark Xcode clean and incremental builds with repeatable inputs, timing summaries, and timestamped `.build-benchmark/` artifacts. Use when a developer wants a baseline, wants to compare before and after changes, asks to measure build performance, mentions build times, build duration, how long builds take, or wants to know if builds got faster or slower.

Use when you need to use Spring Data JDBC with Java records — including entity design with records, repository pattern, immutable updates, aggregate relationships, custom queries, transaction management, and avoiding N+1 problems. This should trigger for requests such as Review Java code for Spring Data JDBC; Apply best practices for Spring Data JDBC in Java code. Part of cursor-rules-java project

Append a structured learning entry to AGENTS_LEARNING.md whenever an AI agent makes a mistake. Auto-activates as a composite skill when: a pre-write skill violation is detected and auto-fixed, or when the session retrospective finds a correction loop. Also triggers directly when the user corrects the AI mid-session. Use when: mistake, wrong, redo, that's not right, correction, my bad, fix that error, I made a mistake, agent error, learning log, log mistake, AGENTS_LEARNING.md

Implement ViewBinding, RecyclerView, and XML layouts correctly on Android. Use when working with XML layouts, ViewBinding, or RecyclerView adapters in legacy Android projects.

Build standalone Angular components with Signals inputs, OnPush change detection, Control Flow, and Smart/Dumb patterns. Use when building standalone Angular components, implementing @if/@for control flow, applying OnPush change detection, or implementing Signals in Angular components.

Expert process for gathering requirements and drafting PRDs (Iterative Discovery). Use when creating a PRD, speccing a new feature, or clarifying requirements.

Implement application state with Angular Signals, computed derivations, and NgRx Signal Store. Use when implementing reactive state with signal(), computed(), effect(), or @ngrx/signals in Angular.

Append a structured learning entry to AGENTS_LEARNING.md whenever an AI agent makes a mistake. Auto-activates as a composite skill when: a pre-write skill violation is detected and auto-fixed, or when the session retrospective finds a correction loop. Also triggers directly when the user corrects the AI mid-session. Use when: mistake, wrong, redo, that's not right, correction, my bad, fix that error, I made a mistake, agent error, learning log, log mistake, AGENTS_LEARNING.md (triggers: AGENTS_LEARNING.md, mistake, wrong, redo, correction, agent error, learning log)

Apply the Google Swift Style Guide to Swift code generation, review, and refactoring. Covers naming, file structure, formatting, and source-backed programming practices. Use for Google Swift compliance, not architecture, framework design, or project policy outside the guide.

Use when you need to refactor Java code to adopt modern Java features (Java 8+) — including migrating anonymous classes to lambdas, replacing Iterator loops with Stream API, adopting Optional for null safety, switching from legacy Date/Calendar to java.time, using collection factory methods, applying text blocks, var inference, or leveraging Java 25 features like flexible constructor bodies and module import declarations. This should trigger for requests such as Review Java code for modern Java development; Apply best practices for modern Java development in Java code. Part of cursor-rules-java project

Use when you need to add or evaluate Maven dependencies that improve code quality — including nullness annotations (JSpecify), static analysis (Error Prone + NullAway), functional programming (VAVR), or architecture testing (ArchUnit) — and want a consultative, question-driven approach that adds only what you actually need. This should trigger for requests such as Add Maven dependencies; Add JSpecify nullness dependencies; Add Error Prone NullAway dependencies; Add VAVR functional dependencies; Add ArchUnit architecture testing dependencies. Part of cursor-rules-java project

Use when you need to write or improve integration tests — including Testcontainers with @ServiceConnection, @DataJdbcTest persistence slices, TestRestTemplate or MockMvcTester for HTTP, data isolation, and container lifecycle management for Spring Boot 4.0.x. This should trigger for requests such as Review Java code for Spring Boot integration tests; Apply best practices for Spring Boot integration tests in Java code. Part of cursor-rules-java project

Use when you need to review, improve, or write Java unit tests — including migrating from JUnit 4 to JUnit 5, adopting AssertJ for fluent assertions, structuring tests with Given-When-Then, ensuring test independence, applying parameterized tests, mocking dependencies with Mockito, verifying boundary conditions (RIGHT-BICEP, CORRECT, A-TRIP), leveraging JSpecify null-safety annotations, or eliminating testing anti-patterns such as reflection-based tests or shared mutable state. This should trigger for requests such as Review Java code for unit tests; Apply best practices for unit tests in Java code. Part of cursor-rules-java project