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Found 2,416 Skills
Creates oh-my-claude statusline plugins from scratch. Use when the user asks to build, create, make, or scaffold a new statusline plugin, segment, or widget for oh-my-claude or Claude Code's statusbar. Handles both JS plugins and script plugins (Python, Bash). Generates the plugin file, tests it, wires it into the statusline, and verifies it renders.
Lobstr.io platform help — no-code web scraping platform with 50+ ready-made scrapers for Google Maps, LinkedIn Sales Navigator, Twitter, YouTube, and more. Features cookie-based login sync, scheduled automation, multi-threading, and a full API with Python SDK and MCP Server. Use when configuring a Lobstr scraper, exporting data to Google Sheets or S3, setting up scheduled scraping, working with the Lobstr API or Python SDK, or managing credits. Do NOT use for general prospect list strategy (use /sales-prospect-list), cross-platform enrichment strategy (use /sales-enrich), or integration strategy (use /sales-integration).
Use when the user explicitly requests security best practices guidance, a security review or report, or secure-by-default coding help for Python, JavaScript or TypeScript, or Go code.
Patterns for robust error handling across TypeScript, Python, and Go. Covers typed errors, error boundaries, retries, circuit breakers, and user-facing error messages.
Alibaba Cloud ECS extension installation skill. Supports querying available extension lists, checking if a specific extension is available, and one-click installation of extensions (e.g., OpenClaw, BT Panel, Python environments, etc.). Extensions are officially provided by Alibaba Cloud with verified installation packages and scripts. Triggers: "extension", "install", "BT Panel", "OpenClaw", "Python", "Node.js", "package", "one-click install"
Pre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
Install Holoscan SDK natively on Ubuntu via apt. Use for C++ installs on Ubuntu; pair with /holoscan-install-wheel for Python.
Multi-agent review-and-improve loop for a GitHub PR you have checked out — posts a "starting" PR comment cc'ing the original author, runs requested rounds plus any adaptive continuation, applies fix commits to the local branch after each round, pushes everything back to the PR, then edits the starting comment in-place with the synthesized report (or a failure summary). Auto-detects the PR from the currently checked-out branch when no locator is supplied. Use when the user wants to "improve a PR", "review and commit fixes", "iterate on my PR", or "review and push back" against a checked-out PR branch. Requires `gh`, `uuidgen`, `jq`, and `uv` or `python3` on PATH. Activates the `review-anvil` engine in per_fix mode.
Use when writing, reviewing, or refactoring code, or scaffolding a new project. Language-agnostic principles (types encode invariants, parse don't validate, errors as values, no mocks, earn abstractions) with dialects for Rust, TypeScript, Go, and Python.
Use for ANY task involving Ultralytics Platform, the ultralytics Python package, yolo CLI, YOLO model weights (.pt), dataset annotation, training, validation, prediction, tracking, export, deployment, or the detect / segment / semantic / depth / classify / pose / OBB vision tasks.
Pre-flight checklist for long-running ML training jobs covering config diff, run naming, path verification, monitoring setup, and restart-cleanup. Use when the user asks to launch, kick off, start, restart, or kill a training run, or mentions launching a multi-hour or multi-day GPU job (python train, accelerate launch, torchrun, deepspeed, sbatch, tmux training).
Finds data scientists and ML engineers to recruit using apidojo's Twitter scrapers on Apify. Triggers when the user asks to: find data scientists on Twitter for recruiting, discover machine learning engineers or AI researchers to hire from X, find data analysts or ML practitioners by specialization on Twitter, identify NLP computer vision or LLM engineers via social signals, find data science professionals open to work on Twitter, build a data science talent pipeline from social, or find researchers posting about job opportunities. Returns handle, name, ML specialty (from bio/tweets), stack (Python/R/TensorFlow), follower count, and open-to-work signals. Ideal for ML engineering hiring managers, AI research labs, and data-driven startups.