Automation and verification guide for running Native SDK apps. Use when the user asks to test a running app, inspect runtime state, list windows, wait for readiness, drive widgets, take deterministic screenshots, send bridge commands, debug why automation is not connected, create smoke tests, or verify a Native SDK example in a GUI-capable session.

Run the japicmp binary-compatibility report for wiremock-core and produce a filtered summary covering only @PublishedAPI-annotated classes. Use this when asked to generate, refresh, or summarise the breaking-changes report.

Produce a scannable review brief for a branch or PR so the maintainer can approve without reading the whole diff. Use when the user asks "how do I review this", "summarize the changes", "what should I look at", or wants to understand a PR in under two minutes.

Generate detailed implementation plans for complex tasks. Creates comprehensive strategic plans in Markdown format with objectives, step-by-step implementation tasks using checkbox format, verification criteria, risk assessments, and alternative approaches. All plans MUST be validated using the included validation script. Use when users need thorough analysis and structured planning before implementation, when breaking down complex features into actionable steps, or when they explicitly ask for a plan, roadmap, or strategy. Strictly planning-focused with no code modifications.

Covers how to configure the maximum allowed size of the Webiny API Lambda bundle using the Infra.Api.MaxBundleSize extension in webiny.config.tsx. Use when a project's API bundle exceeds the default 4.5 MB limit or when you want to enforce a stricter limit. Handles the extension syntax, byte calculations, and interpreting the build error message.

Writes and runs OrchardCore tests — xUnit unit tests, SiteContext-based integration tests, Moq mocking, and Playwright functional tests. Use when the user needs to add a test, set up a test harness/tenant for tests, mock OrchardCore services, or run the test suite.

Builds, watches, and manages frontend assets in OrchardCore. Use when modifying SCSS, JS, TS, or Vue files, adding new assets to a module/theme, or troubleshooting build failures. Covers all asset actions (vite, sass, min, copy, parcel, webpack, concat) and the three-tier package structure.

Change or diagnose Xberg PDF extraction, native/Pdfium backend selection, PDF rendering sessions, encrypted documents, OCR fallback, or backend-specific capability gaps. Load for PDF engine work, not generic image OCR.

Run, diagnose, or change Xberg extraction benchmarks, quality scoring, benchmark fixtures, artifact contracts, and independently sourced ground truth. Load for the Benchmarks workflow or benchmark-harness work, not ordinary unit tests.

Reference: implementation-planning framework for international hiring — EOR vs. entity decision framing, cross-functional triggers for tax/finance/HR, structured outside-counsel briefing requests, and a persistent gap tracker. Loaded by /expansion-kickoff and /expansion-update; not invoked directly.

Pick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to deploy a model to a SageMaker endpoint and an image URI needs to be chosen — including when the user says "deploy this LLM", "host this HuggingFace model", "serve this fine-tuned model", "deploy this embedding model", "host a reranker", "serve a sentence-transformers model", or when about to hardcode any container URI in deployment code. HuggingFace-curated Deep Learning Containers are ALWAYS preferred: HuggingFace vLLM (LLMs and generative rerankers), HuggingFace vLLM-Omni (multimodal), TEI (embeddings/cross-encoder rerankers), HF Inference Toolkit (other transformers). Generic images (AWS vLLM, DJL-LMI, SGLang) are used only when no HuggingFace image is compatible — never merely because they carry a newer version. Never hardcode a container URI from memory and never default to TGI. Prevents stale-image failures and wrong-region URIs.

Ingest MCAP files into Rerun chunk streams with rerun.chunk.McapReader. Read when converting an MCAP recording, selecting topics or decoders, decoding custom protobuf messages, or when an MCAP-derived stream comes out empty. Builds on rerun-chunk-processing (stream mechanics) and rerun-data-model (what the topics should become).

Perform a goal-driven, black-box UX acceptance journey in a browser and report the path, friction, and observable outcome. Use only in an isolated tester context with a supplied start URL and brief.

Use this skill when the user asks to create, scaffold, update, or review a MoviePilot agent skill. This includes adding a new built-in skill under the repository `skills/` directory, editing an existing built-in skill, writing `SKILL.md` frontmatter and workflow instructions, choosing `allowed-tools`, adding helper scripts when needed, and bumping the built-in skill `version` so changes can sync into `config/agent/skills`.

OpenTelemetry best practices for manual instrumentation. Use when adding, changing, or reviewing OpenTelemetry instrumentation in code. Guidance to choose runtime boundaries, choose signals, apply semantic conventions, handle propagation, control cardinality, and verify the result.

Use this skill when contributing to InsForge's backend package. This is for maintainers editing backend routes, services, providers, auth, database logic (including RLS-enforced surfaces like storage and realtime), schedules, or backend tests in the InsForge monorepo.

Wrap up the current session: verify quality gate passed, remind user to commit, archive completed tasks, and record session progress to the developer journal. Use when done coding and ready to end the session.

Bootstrap project-specific Trellis coding specs with a platform-neutral single-agent workflow. Use when creating or refreshing .trellis/spec guidelines, analyzing a codebase with GitNexus, ABCoder, or source inspection, decomposing package/layer spec work, and writing real codebase-backed spec docs without placeholder text.

Guides developers through implementing event and conversion ingestion to Google products using the Data Manager API /v1/events/ingest endpoint and its associated client libraries. Use this skill when the user wants to upload offline conversions, enhanced conversions for leads, click conversions, Google Analytics web or app events, or any other event ingestion use case supported by the Data Manager API. Don't use for uploading audience members (use the data-manager-api-audience-ingestion skill).

Create the required PR-ready summary block, branch suggestion, title, and draft description for ioredis. Must be used before the final response whenever the actual task diff includes runtime code, tests, examples, build/test configuration, or docs with behavior impact, regardless of perceived change size. Skip only when no eligible files changed, every change is repo-meta or docs-only without behavior impact, the task is conversation-only, or the user explicitly opts out.