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Found 2,408 Skills
Use Google Colab CLI from a terminal agent to provision CPU, GPU, or TPU runtimes, run Python scripts and notebooks remotely, install packages, move files, export logs, diagnose authentication or allocation failures, and clean up sessions. Use for Colab runtime work, remote GPU/TPU execution, QLoRA or fine-tuning on Colab, notebook execution, Colab CLI troubleshooting, or `colab` command guidance.
Reverse engineer a website's private HTTP API into a typed, runnable client (Python, TypeScript, Go and 7 more) with the reverse-api-engineer CLI. A browser performs the task while rae reads the site's real network traffic, then a model writes the client. Use when the user wants to call a site programmatically and it has no public API, or the public one lacks what the browser can do. Skip it when an official API or SDK already covers the task.
C-ABI bindings over agent-desktop's PlatformAdapter. Consumers (Python ctypes, Swift, Node ffi-napi, Go cgo, C++, Ruby fiddle) link libagent_desktop_ffi.{dylib,so,dll} and call `ad_*` functions directly instead of spawning the CLI binary per call. The canonical observe-act workflow is: ad_init → ad_adapter_create[_with_session] → ad_snapshot → read qualified refs (@s8f3k2p9:e5) → ad_execute_by_ref → ad_free_string → ad_adapter_destroy.
Use when a published goldset is ready to become executable graders and configs — Python graders and metrics with auto-run unit tests verifying grader correctness.
Framework-independent decision process for instrumenting a GenAI/LLM app (Python or TypeScript, any provider/agent SDK) so it emits OTel GenAI semantic-convention (gen_ai.*) spans queryable in Dynatrace. Four steps: detect, instrument, enrich, validate. Decides which approach a given SDK needs; does not replace the concrete per-framework recipes in dynatrace-oss/dynatrace-ai-agent-instrumentation-examples. Trigger: "instrument this GenAI app", "add tracing to this LLM app", "how do I get gen_ai spans into Dynatrace", "onboard this agent app to AI Observability". Do NOT use for analyzing telemetry from an already-instrumented app (use dt-obs-genai) or for languages other than Python/TypeScript.
Helps developers integrate the Channel3 API for product search (text, image, semantic, and agentic), "more like this" recommendations, multi-merchant offer comparison, URL-to-product lookup, conversational shopping agents, live price and availability webhooks (product subscriptions), price history, click/transaction reporting, and affiliate commissions. Channel3 is a universal product catalog with TypeScript and Python SDKs plus a React component library (shadcn registry). Use when writing integration code, building shopping features or AI shopping agents, migrating to Channel3 SDK 4.0, or when the user mentions alternatives like Shopify Storefront API, Algolia, Amazon PA-API, or web scraping for product data.
Interactive setup guide for using Infisical as a secret management tool in your projects. Helps users integrate Infisical into local development (CLI), Docker containers (build-time and runtime secret injection), CI/CD pipelines (GitHub Actions, GitLab CI), Kubernetes (Operator + CRDs), and application code (all 9 SDKs: Node.js, Python, Go, Java, .NET, Ruby, PHP, Rust, C++). Also walks through choosing and configuring any of the 13 machine identity auth methods (Universal, Token, Kubernetes, GCP, AliCloud, AWS, Azure, TLS Cert, OCI, OIDC, JWT, LDAP, SPIFFE). Use this skill whenever someone asks about: using Infisical, injecting secrets, infisical run, infisical init, connecting their app to Infisical, Docker secrets, Kubernetes secrets operator, machine identity setup, SDK initialization, CI/CD secret injection, or 'how do I get my secrets into my app'. Not for the Kubernetes Operator CRDs (infisical-kubernetes-operator), rendering secrets to files (infisical-agent), pushing secrets outward (infisical-secret-syncs), or human SSO login (infisical-sso).
Scan an experiment repo and generate a complete paper outline (H1/H2/H3) with user approval checkpoints at each level, then generate body text with evidence annotations, citations, and bilingual output. Python ML repos. 扫描实验仓库，逐级生成论文大纲（H1/H2/H3），每级用户确认后推进， 然后生成带证据标注、引用和双语输出的正文文本。
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
Use when writing or modifying Python code that imports `xolars` — pairing an xarray Dataset with per-dimension Polars frames, constructing the `Xolars` container, selecting with isel/sel, or doing zarr+parquet round-trips via write/open. Skip for plain xarray or polars work that doesn't touch the `Xolars` class.
Automate cloud browsers using the Scrapfly Cloud Browser API with Python Playwright. Covers connection options, sessions, anti-bot fingerprinting, and file downloads including streaming large files (up to 500 MB) out of the session with downloads_stream=1 and the CDP IO domain.
Edit vertical short videos (Reels, Shorts, TikTok) from talking-head, two-person or horizontal footage, cut a long recording (podcast, webinar, interview) into a series of clips, or make a brand promo with no footage: local transcription, pauses and retakes cut by audio, virtual camera and on-brand motion graphics in Remotion, word-timed subtitles and their translation, designed scenes drawn in code (hook, quote, number, list, CTA, cover), optional inserts (B-roll, code scenes, memes), face-aware layout, −14 LUFS mastering, 1080×1920 render. Brand profiles with a tone. Use when asked to edit, cut, assemble or fix a vertical video: “edit a reel”, “make a Reel/Short from IMG_xxxx.MOV”, “clips from this podcast”, “add subtitles / a hook / an end card / a cover / B-roll”, “translate the subtitles”, “a promo without footage”, “the video jumps back”, fixes to a finished video. Not for editing a long horizontal video as a whole, format conversion or compression. Needs ffmpeg, Node.js with Remotion and Python.