Browse reusable Agent Skills, each with a clear purpose and practical guidance.
21 production-ready scripts for iOS app testing, building, and automation. Provides semantic UI navigation, build automation, accessibility testing, and simulator lifecycle management. Optimized for AI agents with minimal token output.
Interprets `@preact/signals-debug` updates and the AI-native Vite event stream to diagnose reactive UI bugs.
Use when creating, editing, fixing, or reviewing tests; when adding mocks, fakes, assertions, unit tests, PG integration tests, frontend component tests, or Playwright e2e tests; or when changing tests after failures.
This skill should be used when a Seedance 2.0 output is blurry, jittery, off-prompt, morphing, blocked, visually generic, unstable, desynced, inconsistent, or otherwise fails and needs root-cause diagnosis.
Write tests for Apache Iggy connectors - sinks, sources, transforms, SDK, runtime. Covers BDD unit-test naming, the canonical source state round-trip tests, and the real-infra integration test layout under `core/integration/tests/connectors/` with `testcontainers-modules` + `#[iggy_harness]`. Load when writing or reviewing tests in `core/connectors/` or `core/integration/tests/connectors/`. Use for connector test authoring. NOT for runtime internals or non-connector test patterns.
Analyze a problem and provide a detailed explanation of the issue, root cause, proposed fix, and verification steps.
Find, triage, and fix production errors captured by Datadog Error Tracking, then open a PR. Use when asked to look at "Datadog issues/incidents/errors", "find and fix bugs from Datadog", investigate the most-frequent or newest production errors, or work a specific Datadog Error Tracking issue.
Triages a PR with GitHub CLI: loads issue-level and inline review feedback (gh pr view, gh api REST, gh api graphql as appropriate), walks items in order, replies in the correct thread, optional resolve. Groups duplicate comments into one fix. Use when addressing PR review comments, Copilot inline threads, or babysitting PR feedback.
Run profile-driven bottleneck optimization across Apache Fory implementations (Java, C++, Python/Cython, Go, Rust, Swift, C#, JavaScript/TypeScript, Dart, Kotlin, Scala). Use when improving serialize/deserialize throughput or latency, recovering regressions against a reference commit, diagnosing flamegraphs, fixing perf-related CI failures, or porting proven optimizations across languages without protocol or API regressions.
Run and interpret scripts/smoke_test.sh, the on-demand checks for optional dependencies that CI and the default docker compose don't cover: the Postgres and MongoDB checkpointers, the AG-UI endpoint, and LangFuse tracing. Use when you've touched the memory/checkpointer layer, service startup/health, the AG-UI adapter, LangFuse tracing, or bumped one of those dependencies — and want to confirm the real integration still works without waiting for a full CI run. Also use when deciding WHETHER such a check is even warranted for a change.