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Found 1,812 Skills
Upload one or many videos to YouTube. Use when the user wants to "上传到 YouTube", "发 YouTube", "批量上传", "upload to YouTube", "post videos to YouTube", or to publish a finished `final/` directory of MP4s. Reads per-video metadata (title / description / tags) from a sibling `UPLOAD_META.md` file when present (the user's standard markdown format), or from command-line flags. Survives behind a SOCKS/HTTP proxy by using `requests` directly for the resumable upload (the stock `google-api-python-client` MediaFileUpload stalls under this user's proxy setup).
Generate images with gpt-image-2 through an OpenAI-compatible Image API using the current OPENAI_API_KEY, OPENAI_BASE_URL, or CUSTOM_IMAGE_URL environment variables. Use when the user asks to call gpt-image-2 via API/CLI, /v1/images/generations, the prior /api/image/generate endpoint flow, or wants the faster API route instead of Codex CLI image_generation/session extraction.
Reference guide for CLI-Anything, which auto-generates production-ready agent-controllable CLI harnesses for any GUI application via a 7-phase.
Designs and reviews Forze dependency keys, Deps containers, routed/plain registrations, lifecycle steps, and custom DepsModule implementations. Use when authoring adapters, adding integration modules, or debugging dependency resolution and StrEnum route wiring.
Queries Huawei Cloud billing and pricing. Covers balances, bills, coupons, cash coupons, stored-value cards, orders, refunds, costs, free resources, resource usage, enterprise accounts, and on-demand/period/ELB/NAT/DCS pricing. No write operations. Use this skill when the user needs to check fees, view bills, estimate prices, review coupon balances, query orders, or get consumption stats. Triggers: 华为云计费, 账单, 余额, 优惠券, 代金券, 储值卡, 订单, 退款, 成本, 资源用量, 询价, 定价, 费用查看, 账单明细, 价格估算, 消费统计, billing, pricing, cost.
MCP server for accessing Monarch Money personal finance data through Claude Desktop and Claude Code
Read-only Storage Analysis Assistant for macOS / Windows (auto-detects system). Scans the entire disk usage to identify space hogs, categorizes each item into three levels: 🟢 Auto-cleanable / 🟡 Manual judgment required / 🔴 Clean with caution, and provides actionable disposal plans. Generates an interactive HTML report with beautiful formatting, collapsible sections, and one-click copy commands. Also supports starting a local service to delete files directly via the web (move to trash / delete immediately). The entire scanning process is read-only. Must be used in the following scenarios: When users mention "storage analysis", "disk full", "C drive/hard disk full", "insufficient space", "clean up space", "disk cleanup", "space occupied", "what's taking up space", "help me check storage", "check computer storage/space", "storage space", "computer space insufficient", "memory full/insufficient" (in Chinese colloquial, "memory" often refers to storage), "storage analysis", "disk cleanup", "clear cache", "disk cleanup"; or when users complain about insufficient computer space, want to know what's taking up hard disk space, or need cleanup suggestions. Note: If users explicitly refer to RAM (e.g., "which process is using memory", "high memory usage", want to see Activity Monitor), that's RAM, not storage, and does not belong to this skill.
YouTube transcripts to summaries, threads, blogs.
Decide where files live in an ML experimentation project: reusable code in `src/<pkg>/`, one `# %%` script per experiment in `experiments/`, design notes + index in `journal/`, reports in `reports/`, agent-only probes in `scratch/`, narrative digest in `overview/summary.md`. Owns the layout, the file-creation rules (one file per experiment, ask before editing), and the jupytext `# %%` script convention. Never imposes `data/` — the user owns that. TRIGGER — any of: - Starting a new ML project / scaffolding a workspace. - About to create the first experiment file in a project. - About to create `src/<pkg>/data.py` / `features.py` / `pipeline.py` / `evaluate.py` for the first time. - About to write a `.ipynb` for experimentation — redirect to a `# %%` script under `experiments/`. - User asks where something should live, how to organize the project, or how to set up the workspace. - About to add a new experiment iteration — decide new file vs edit existing (ask the user). SKIP when: the file is clearly part of an already-populated module (e.g., adding a function to existing `features.py`); pure refactor inside a single existing file; pipeline declaration mechanics (`build-ml-pipeline`); evaluation mechanics (`evaluate-ml-pipeline`); skore symbol lookup (`python-api`). HOW TO USE: **first run the Detection table** below — if any signal matches, glue to existing conventions (do not rename or move folders). If no signal matches, scaffold the default layout. **Emit the Pre-flight checklist as visible text and read the Stop conditions before any file is created or edited.** Use templates in `templates/`; copy and adapt, do not rewrite from scratch.
Use when the user wants to create a dataset, generate synthetic data, or build a data generation pipeline.
Medicinal chemistry filters. Apply drug-likeness rules (Lipinski, Veber), PAINS filters, structural alerts, complexity metrics, for compound prioritization and library filtering.
Generates GitHub Actions CI workflow configuration