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 4 ore
44.573 de skill-uri
- gsd:reviewdavepoon/buildwithclaudeRequest cross-AI peer review of phase plans from external AI CLIsInginerieFără avertismente★ 3,7 K↓ —
- hypothesis-generationforyourhealth111-pixel/Vibe-SkillsStructured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Also owns explicit HypoGeniC-style or automated LLM-driven hypothesis generation/testing requests inside this single skill. For open-ended ideation use scientific-brainstorming.TestareFără avertismente★ 3,8 K↓ —
- airtable-automationdavepoon/buildwithclaudeAutomate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.ProductivitateFără avertismente★ 3,7 K↓ —
- ad-angle-researchdavepoon/buildwithclaudePull the ads a competitor is running right now on Meta (Facebook/Instagram) and Google, then extract the hooks, offers, CTAs and landing pages worth modelling. Use when writing ad copy, planning creative tests, choosing a landing page angle, or when the user asks "what is X advertising", "what ads does X run", "find competitor ad hooks". Reads live Ad Library and Ads Transparency data through the Tracetify MCP; falls back to a manual Ad Library walkthrough when the connector is absent.ȘtiințăFără avertismente★ 3,7 K↓ —
- networkxforyourhealth111-pixel/Vibe-SkillsComprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.ȘtiințăFără avertismente★ 3,8 K↓ —Apare și în 1 alt depozit
- research-grantsforyourhealth111-pixel/Vibe-SkillsWrite competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.ȘtiințăFără avertismente★ 3,8 K↓ —
- nemo-retrieverNVIDIA/skillsUse when searching, extracting, ingesting, or querying a document collection with the NeMo Retriever 26.8.1 CLI, including local LanceDB indexes and deployed Retriever services. Use for PDFs, images, Office files, HTML, text, audio, and video; not for editing documents or web search.DevOpsFără avertismente★ 3,7 K↓ —
- wiki-dedupAr9av/obsidian-wikiDetect and merge wiki pages representing the same concept under different names. Use for page-identity deduplication and consolidation. Destructive merges require confirmation; not for link repair or general linting.AlteleFără avertismente★ 3,6 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↓ —
- umap-learnforyourhealth111-pixel/Vibe-SkillsUMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.AlteleFără avertismente★ 3,8 K↓ —Apare și în 1 alt depozit
- ml-pipeline-workflowforyourhealth111-pixel/Vibe-SkillsBuild end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.ProductivitateFără avertismente★ 3,8 K↓ —Apare și în 1 alt depozit
- doca-flow-tuneNVIDIA/skillsUse this skill when the user is tuning a live or captured `doca-flow` pipeline with `doca_flow_tune` — snapshotting pipe / counter / KPI state, picking a tuning axis (rule placement, resource hints / table sizing, HW-offload mode) and a matching measurement (rule-install rate, lookup latency, hardware-counter delta), running offline or online (read-only or state-changing) modes, reading the dumper CSV / analyze JSON / visualize mermaid, or applying a recommendation back into the Flow program. Trigger even when the user does not explicitly mention "doca_flow_tune" — typical implicit phrasings include "Flow rule-install rate is low on BlueField", "table sizing looks wrong for this pipe", "tune visualize step is empty", "before/after counters don't move", or "which doca-flow knob does this recommendation hit". Refuse and route elsewhere for measuring baseline numbers (doca-flow-perf, doca-flow-dpa-perf), writing the doca-flow application, DOCA install, or streaming Flow telemetry — those belong to other skills.DateFără avertismente★ 3,7 K↓ —
- vector-forgetrailofbits/skillsMutation-driven test vector generation. Finds implementations of a cryptographic algorithm or protocol, runs mutation testing to identify escaped mutants, then generates new test vectors that deliberately exercise the uncovered code paths. Compares before/after mutation kill rates to prove vector effectiveness. Use when generating cryptographic test vectors, measuring Wycheproof coverage gaps, finding escaped mutants via mutation testing, creating cross-implementation test suites, or improving test vector coverage for crypto primitives.TestareFără avertismente★ 7,8 K↓ —
- green-screenZJU-REAL/Easel绿幕抠像 / 换背景 / 合成：把绿幕（或蓝幕/指定色）拍摄的前景人物抠出来，合成到新背景——图片、视频、纯色或前景自身模糊。当用户说 绿幕、抠像、抠图换背景、去绿幕、chromakey、绿幕合成、换背景、蓝幕、把绿幕背景换掉、人物抠出来、绿布 时使用。基于 shared/scripts/chromakey.py（ffmpeg chromakey + despill）。与 video-reframe 区别：reframe 只改画幅不换背景；与 ai-image-gen 区别：那个生成新图，本 SKILL 处理已拍的绿幕素材。MediaFără avertismente★ 4,1 K↓ —
- pr-improvertrailofbits/skillsRuns an autonomous review-and-fix improvement loop over the current branch's changes until a PR review comes back clean, scoped mechanically to the directories the branch touched. Reviews are performed by an installed PR-review skill (default: pr-review-toolkit's review-pr). Use to fix review findings on a branch before opening or updating a pull request ('clean up this branch', 'fix this PR until review passes', 'run review-and-fix on my changes'). NOT for a one-time review — run the PR-review skill directly.InginerieFără avertismente★ 7,8 K↓ —
- doca-sha-offload-engineNVIDIA/skillsUse this skill when wiring the DOCA SHA Offload Engine (an OpenSSL ENGINE) into an existing OpenSSL pipeline to offload one-shot SHA-1, SHA-256, or SHA-512 (EVP_Digest) onto DOCA SHA hardware without rewriting against doca-sha. Covers engine load mechanics (`openssl engine dynamic`, `set_pci_addr` ctrl, `-engine_impl`), the SHA-224 negative test that proves offload engaged, the message-size window where offload beats CPU SHA, and engine-vs-library selection. Trigger even when the user does not say "DOCA SHA Offload Engine" or "OpenSSL ENGINE" — typical implicit phrasings: "speed up openssl SHA on BlueField", "offload SHA without code changes", "is openssl using the accelerator or falling back to software", "prove DOCA SHA actually ran", "openssl dgst hashed but I'm not sure it was offloaded". Refuse and route elsewhere for new SHA pipelines (use doca-sha), MD5 / SHA-3 / SHA-224 / HMAC-SHA offload, incremental hashing via chained `EVP_DigestUpdate`, or OpenSSL PROVIDER authoring.TestareFără avertismente★ 3,7 K↓ —
- kiro-discoverygotalab/cc-sddEntry point for new work. Determines the best action path or work decomposition (update existing spec, create new spec, mixed decomposition, or no spec needed) and refines ideas through structured dialogue.PlanificareFără avertismente★ 3,7 K↓ —
- opendavepoon/buildwithclaudeBoot the session, load context from the vault, and surface what mattersProductivitateFără avertismente★ 3,7 K↓ —
- doca-comm-channel-adminNVIDIA/skillsUse this skill to enumerate host↔DPU DOCA comch (formerly Comm Channel) servers and connections via the shipped doca_comm_channel_admin binary — listing comch-capable devices and decoding the per-device server / connection table (server name, PID, in-use / max, PCIe address). The shipped binary is a SINGLE-SHOT SCAN-AND-PRINT tool with no registered arguments — NO list / inspect / drain / restart subcommands; one inventory pass over every comch-capable doca_dev on this side. Channel reset / drain / restart go to doca-comch (program side), doca-setup / doca-hardware-safety (driver reload), or BFB / RShim — NOT to this binary. Trigger on phrasings like "list comch servers", "which channels are active on this BlueField", or "verify admin tool sees same channel as program." Refuse and route elsewhere for the comch programming API, library install, protocol design, channel reset, or general orientation.DesignFără avertismente★ 3,7 K↓ —
- wiki-queryAr9av/obsidian-wikiSearch and synthesize answers from the compiled Obsidian wiki, including cited and multi-hop answers. Use for questions about existing wiki knowledge or fast index-only lookups, and for challenge requests ("challenge this", "argue against X", "poke holes in my plan") that look for the vault's own evidence against a plan. Supports named-vault routing such as wiki-query @work; not for ingesting new sources.PlanificareFără avertismente★ 3,6 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↓ —
- gsd:managerdavepoon/buildwithclaudeInteractive command center for managing multiple phases from one terminalAlteleFără avertismente★ 3,7 K↓ —
- short-drama-assetszenstory-ai/drama-skills从短剧剧本拆出人物/造型、地点/视图、道具/状态和跨场连续性，写成创作者可读的视觉设定。用户说“拆角色/场景/道具”“做资产设定”“判断复用还是新变体”“更新造型/道具状态”，或拿现成剧本直接做视觉资产准备时使用；不写图片提示词，不生成媒体。AlteleFără avertismente★ 3,3 K↓ —
- golang-modernizesamber/cc-skills-golangModernize Golang code to use recent language features, standard library improvements, and idiomatic patterns. Use when reviewing Go code with old-style patterns, when encountering a deprecation warning, or when the user asks for modernization, a Go version upgrade (e.g. to Go 1.27), or a CI/tooling refresh. Not for structural refactors, extracting functions, or moving code between packages (→ See `samber/cc-skills-golang@golang-refactoring` skill).InginerieFără avertismente★ 3,6 K↓ —
poster-hero
ZJU-REAL/Easel
AlteleActualizat acum 12 ore
De la autor
生成 1080×1920 竖版营销海报，包含大标题、核心卖点和可选二维码，适合产品发布、活动宣传与朋友圈传播。当用户说“做竖版营销海报、活动宣传图、朋友圈海报、产品发布海报”时使用。横版金句卡用 card-quote，小红书知识卡用 card-xiaohongshu。
Instalare
npx skills add ZJU-REAL/Easel --skill poster-hero -a claude-code
Se instalează în .claude/skills/poster-hero/ · 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 instrucțiuniFolosește rețeauaLicență: APACHE-2.0
Verificări de siguranță pe SKILL.md
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De ce 90
Securitate100
Proveniență83
Întreținere100
Licență100
Adopție57
Fișiere (4)
- EASEL-META.md
- SKILL.md
- example.html
- example.md