Skill-uri pentru agenți pe care le poți verifica înainte să le instalezi
Skill-uri SKILL.md publice din depozite GitHub cu peste 50 de stele și de la producători, scanate și evaluate. Instalează oricare dintre ele cu o singură comandă în Claude Code, Cursor, Codex, GitHub Copilot sau Gemini CLI.
45.604 skill-uri din 2.205 depozite · actualizat acum 20 de ore
45.604 skill-uri
- message-house-builderaaron-he-zhu/aaron-marketing-skillsUse when the user asks to "build a message house", "write a PR-FAQ for our launch", or "define the launch narrative and value pillars"; derives from the positioning canvas a message house — tagline, one-liner, three value pillars, per-persona proof points (each labeled Measured / User-provided / [needs source]) — plus a working-backwards PR-FAQ narrative spine (launch-day tense, empty-chair test, five external + five internal FAQs) and per-channel message angle packs (angles, not finished copy). Not for the positioning canvas itself — use positioning-mapper; not for finished blog posts or pages — use content-writer; not for ad or email units — use each discipline creative builder; not for claim adjudication — use offer-claims-registry. 消息屋/PR-FAQ/价值支柱/发布叙事TestareFără avertismente★ 3 K↓ —
- launch-asset-packageraaron-he-zhu/aaron-marketing-skillsUse when the user asks to "package the launch assets", "build a press kit", or "prep the store listing and go-live checklist"; produces a tier-scoped launch asset manifest with production status — a press kit spec (factsheet, description, history, features, videos, images, logo and icon, awards, contact), demo script and screenshot specs, a launch FAQ, dual-store listing metadata drafts against the official character budgets (per App Store Connect / Play Console documentation), and a technical go-live checklist manifest (robots flip, sitemap, OG tags, analytics verification — execution stays with technical-seo-checker and serp-markup-builder). Not for the message copy itself — use message-house-builder or content-writer; not for landing page UX — use landing-optimizer; not for keyword research beyond the store surfaces — use keyword-research. 发布资产打包/press kit/商店listing规格/上线检查清单DateFără avertismente★ 3 K↓ —
- gsd:cleanupdavepoon/buildwithclaudeArchive accumulated phase directories from completed milestonesAlteleFără avertismente★ 3,7 K↓ —
- drill-medavepoon/buildwithclaudeTeach the user a topic as an adaptive tutor — retrieval practice, spaced repetition with decay, and persistent memory in ~/.drill-me/. Use when the user wants to learn or be drilled on something, says "drill me on X", "teach me X", or wants to study a topic, a codebase, or a document.ProductivitateFără avertismente★ 3,7 K↓ —
- holoscan-install-sourceNVIDIA/skillsBuild and verify Holoscan SDK 5.x from an explicit source ref with the repository run wrapper; use for Early Access or SDK development.AlteleFără avertismente★ 3,7 K↓ —
- voice-dossier-builderaaron-he-zhu/aaron-marketing-skillsUse when the user asks to "codify how our founder sounds", "build a founder voice dossier", or "set our content pillars"; runs an 80%-extraction interview over the user's OWN posts, emails, and decks (never competitor scraping, never an invented persona) and produces the versioned voice record — a per-platform register map (incl. 小红书/微信公众号), banned phrases, per-context disclosure lines (the ECHO C2 upstream), a few-shot bank built exclusively from own posts, and 3-5 content pillars with Estimated %-allocations — submitted via memory/events/channels.ndjson for channel-registry to store as voice-dossier.md, the record every Craft-phase skill reads first. Not for the brand-level voice canon — use brand-language-codifier; not for audience/persona research — use audience-mapper. 声音档案/品牌语气/创始人语气/内容支柱/披露声明BrowserFără avertismente★ 3 K↓ —
- gsd:managerdavepoon/buildwithclaudeInteractive command center for managing multiple phases from one terminalAlteleFără avertismente★ 3,7 K↓ —
- basecamp-automationdavepoon/buildwithclaudeAutomate Basecamp project management, to-dos, messages, people, and to-do list organization via Rube MCP (Composio). Always search tools first for current schemas.AlteleFără avertismente★ 3,7 K↓ —
- jetson-video-capabilityNVIDIA/skillsUse when Jetson codec, profile, chroma, bit-depth, dimension, engine-count, or operational support must be reconciled from live APIs, authenticated NVIDIA samples, and NVIDIA documentation; also applies the content-DRM scope.MediaFără avertismente★ 3,7 K↓ —
- card-quoteZJU-REAL/Easel生成适合微博、知乎、公众号或 X/Twitter 分享的 16:9 横版金句卡和数据卡。当用户说“做金句卡、语录卡、数据卡、横版分享卡”时使用。小红书竖版知识卡用 card-xiaohongshu，竖版营销海报用 poster-hero。AlteleFără avertismente★ 4,1 K↓ —
- complexa-targetNVIDIA/skillsAdd, edit, inspect, or validate Proteina-Complexa target definitions for protein binders, ligand binders, and AME motif scaffolding. Use for target registries, chain/residue selectors, hotspots, ligand fields, and incomplete motif inputs. Covers direct YAML edits and complexa target/validate target commands; running a campaign with an already registered target belongs to complexa-design.DesignFără avertismente★ 3,7 K↓ —
- tao-train-pointpillarsNVIDIA/skillsPointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D detection — used in autonomous driving and robotics. Use when training, evaluating, exporting, pruning, retraining, or running inference for a TAO PointPillars model. Trigger phrases include "train PointPillars", "LiDAR 3D detection", "point-cloud object detection", "pillar-based 3D detector".MediaFără avertismente★ 3,7 K↓ —
- tao-train-nvpanoptix3dNVIDIA/skillsNVPanoptix3D for panoptic 3D scene reconstruction from posed RGB images. Produces 3D panoptic segmentation (semantic, instance, and panoptic masks) with occupancy completion. Built on a VGGT backbone with a Mask2Former-style head and 3D frustum reconstruction. Use when training, evaluating, exporting, or running inference for a TAO NVPanoptix3D model. Trigger phrases include "train NVPanoptix3D", "panoptic 3D reconstruction", "3D scene segmentation", "occupancy completion".AlteleFără avertismente★ 3,7 K↓ —
- pathmlforyourhealth111-pixel/Vibe-SkillsComputational pathology toolkit for analyzing whole-slide images (WSI) and multiparametric imaging data. Use this skill when working with histopathology slides, H&E stained images, multiplex immunofluorescence (CODEX, Vectra), spatial proteomics, nucleus detection/segmentation, tissue graph construction, or training ML models on pathology data. Supports 160+ slide formats including Aperio SVS, NDPI, DICOM, OME-TIFF for digital pathology workflows.DocumenteFără avertismente★ 3,8 K↓ —
- trailmark-summarytrailofbits/skillsRuns a Trailmark summary analysis on a codebase. Returns auto-detected languages, entry point count, and dependency list. Use when vivisect or galvanize needs a quick structural overview. Triggers: trailmark summary, code summary, structural overview.ProductivitateFără avertismente★ 7,8 K↓ —
- ulw-loopcode-yeongyu/oh-my-openagentA goal-like loop that decomposes work into systematic, evidence-bound ultrawork steps. Use when the user wants a goal loop or durable, checkpointed execution.AlteleFără avertismente★ 70,3 K↓ —
- tao-train-oneformerNVIDIA/skillsOneFormer for universal image segmentation. Unifies panoptic, instance, and semantic segmentation with a single architecture using task-conditioned queries. Use when training, evaluating, exporting, quantizing, or running inference for a TAO OneFormer model. Trigger phrases include "train OneFormer", "universal segmentation", "task-conditioned segmentation", "panoptic / instance / semantic in one model".MediaFără avertismente★ 3,7 K↓ —
- kiro-spec-tasksgotalab/cc-sddGenerate implementation tasks for a specificationPlanificareFără avertismente★ 3,7 K↓ —
- tao-train-bevfusionNVIDIA/skillsBEVFusion for multi-sensor 3D object detection. Fuses LiDAR point clouds and camera images in bird's-eye-view (BEV) space, used in autonomous driving for robust 3D perception. Use when training, evaluating, or running inference for a TAO BEVFusion model. Trigger phrases include "train BEVFusion", "LiDAR + camera fusion", "BEV 3D detection", "multi-sensor 3D perception".AlteleFără avertismente★ 3,7 K↓ —
- tao-launch-workflowNVIDIA/skillsThe mandatory pre-launch gate and four-verb execution contract for every TAO workflow or action. Invoke BEFORE launching anything side-effecting — AutoML, train, evaluate, inference, export, TensorRT engine generation, or DEFT/application workflows — on any execution platform. Covers platform selection, credentials, image confirmation, dataset intake, preflight, the launch review, job records, monitoring, and failure/retry classification. Trigger phrases include "train this model", "run AutoML", "launch on SLURM/docker/k8s/brev/virtualenv", "evaluate my checkpoint", "start a TAO job".ProductivitateFără avertismente★ 3,7 K↓ —
- nvshmem-get-startedNVIDIA/skillsUse when NVSHMEM beginners want a tutorial-style overview on assessment, mental models, first C/C++ or Python NVSHMEM programs, compilation, launching, and next steps.InginerieFără avertismente★ 3,7 K↓ —
- gsd:healthdavepoon/buildwithclaudeDiagnose planning directory health and optionally repair issuesPlanificareFără avertismente★ 3,7 K↓ —
- nemoclaw-user-guideNVIDIA/skillsGuides human users' AI agents to the NemoClaw docs MCP server and canonical Fern documentation in Markdown form. Use when users ask how to install, configure, operate, troubleshoot, secure, or learn NemoClaw with an AI coding assistant. Trigger keywords - nemoclaw docs, use nemoclaw with ai agent, nemoclaw mcp docs, nemoclaw install help, nemoclaw quickstart, nemoclaw markdown docs, llms.txt, agent skills.InginerieFără avertismente★ 3,7 K↓ —
- audio-mixZJU-REAL/Easel音频混合 / 混音：把旁白口播 + 背景音乐 + 音效混成一轨，BGM 自动循环补足并可闪避（旁白说话时自动压低 BGM 保证人声清晰）。当用户说 混音、音频混合、旁白加背景音乐、配音加BGM、人声和音乐混一起、加音效、音频叠加、BGM 压低、闪避、ducking、把配音和bgm合起来 时使用。基于 shared/scripts/audio_mix.py。与 audio-editing concat 区别：concat 是前后顺序拼接，本 SKILL 是同时叠加混音；与 video-editing bgm 区别：那个给视频配乐，本 SKILL 输出纯音频。MediaFără avertismente★ 4,1 K↓ —
scientific-data-preprocessing
foryourhealth111-pixel/Vibe-Skills
ȘtiințăActualizat acum 23 de ore
De la autor
⚠️ CRITICAL USER EXPERIENCE-BASED SKILL - ALWAYS CONSULT BEFORE DATA PREPROCESSING ⚠️ Prevents catastrophic errors (88.9% error rate in V1.0 case study) through multi-level feature analysis, data leakage detection, and semantic validation. MANDATORY for: data preprocessing, feature engineering, standardization, normalization, interpolation, missing value handling, feature selection, or ANY data transformation task. Covers grouped time-series, cross-sectional, panel data. Detects: time travel leakage, causal inversion, ID misuse, semantic-numeric fallacies, distribution blindness. User's hard-won lessons from real project failures.
Instalare
npx skills add foryourhealth111-pixel/Vibe-Skills --skill scientific-data-preprocessing -a claude-code
Se instalează în .claude/skills/scientific-data-preprocessing/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Descarcă .zip
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Doar instrucțiuniNu am văzut acces la rețeaLicență: APACHE-2.0
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 90
Securitate100
Proveniență83
Întreținere100
Licență100
Adopție57
Fișiere (8)
- README.md
- SKILL.md
- UPDATE_LOG_V1.1.md
- references/ai-common-pitfalls.md
- references/decision-trees.md
- references/error-case-studies.md
- references/index.md
- references/validation-checklist.md