Infers likely loop invariants and function contracts by observing execution traces, synthesizing candidates, and checking them inductively. Use when a verifier rejects a loop because the invariant is missing or too weak, when a Daikon-style tool is needed, or before translating code to a verification language.

Generates deployment pipelines with environment promotion, approval gates, and rollback triggers based on target infrastructure. Use when wiring automated deployments from CI to staging/production, when the user asks for a release pipeline, or when adding promotion gates to an existing deploy workflow.

Generates JUnit regression tests that lock in current behavior before a refactor, capturing observed outputs as assertions so that any behavioral change trips a test. Use before large refactors, when inheriting untested legacy Java, or when the spec is "whatever it does now."

Updates broken pytest tests after intentional code changes — triaging assertion failures from mock-coupling failures from genuine regressions, using Python's introspection to automate where safe. Use when a refactor or API change leaves a pile of failing tests and you need to decide update vs. fix vs. delete.

Generates hardened, multi-stage Dockerfiles with non-root users, minimal base images, and a .dockerignore, after auto-detecting the application stack. Use when containerizing an application for the first time, when the user asks for a Dockerfile, when migrating from a VM deployment, or when an existing Dockerfile runs as root, uses a fat base image, or leaks build tooling into the runtime layer.

Executes refactorings — extract method, inline, rename, move — in small, behavior-preserving steps with a test between each. Use when the user wants to restructure working code, when cleaning up after a feature lands, or when a smell has been identified and needs fixing.

Derives executable test cases directly from requirements (user stories, acceptance criteria, specs) by extracting testable conditions, enumerating equivalence classes and boundaries, and producing a traceability map from each test back to its source requirement. Use when building acceptance tests from a spec, when checking whether requirements are covered by existing tests, when translating Gherkin or plain-English criteria into code, or when proving coverage for compliance.

Extracts a TLA+ specification from concurrent or distributed code, modeling the state machine, actions, and fairness conditions for model checking with TLC. Use when verifying concurrency properties of production code, when designing a protocol and wanting to check it before implementation, or when the user has a race condition and needs to prove the fix.

Verifies that a refactoring or transformation preserved observable behavior by comparing before and after execution, differential testing, or I/O capture. Use after a refactoring, after automated code transformation, before merging a structural PR, or whenever the claim is that two code versions do the same thing.

Translates natural-language or pseudocode descriptions of concurrent and distributed systems into TLA+ specifications ready for the TLC model checker. Identifies state variables, actions, type invariants, safety properties, and liveness properties from the description. Use when formalizing a protocol, when the user describes a distributed algorithm to verify, when designing a consensus or locking scheme, or when starting formal verification of a concurrent system.

Applies the SZZ algorithm to VCS history to identify which commits introduced bugs by correlating bug-fix commits with earlier changes. Use when mining a repository for bug-introducing commits, when building a defect-prediction dataset, or when the user asks which commit introduced a given fixed bug.

Translates an entire module or package between languages, handling imports, file layout, visibility, and cross-function dependencies that single-function translation misses. Use when porting a library, when a migration spans multiple files, or when the user hands you a directory and a target language.

Migrates a Spring MVC application to Spring Boot, converting XML config to auto-configuration, restructuring the project, and replacing container deployment with embedded. Use when modernizing a legacy Spring app, when moving off a standalone servlet container, or when the user has web.xml and wants application.yml.

Use XcodeBuildMCP to build, run, launch, and debug the current iOS project on a booted simulator. Trigger when asked to run an iOS app, interact with the simulator UI, inspect on-screen state, capture logs/console output, or diagnose runtime behavior using XcodeBuildMCP tools.

Generates test files, creates mocking strategies, analyzes code coverage, designs test architectures, and produces test plans and defect reports across functional, performance, and security testing disciplines. Use when writing unit tests, integration tests, or E2E tests; creating test strategies or automation frameworks; analyzing coverage gaps; performance testing with k6 or Artillery; security testing with OWASP methods; debugging flaky tests; or working on QA, regression, test automation, quality gates, shift-left testing, or test maintenance.

Analyzes article structure, identifies positions requiring visual aids, generates illustrations with Type × Style × Palette three-dimension approach. Use when user asks to "illustrate article", "add images", "generate images for article", or "为文章配图".