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.
48.168 de skill-uri din 2.325 de depozite · actualizat acum 10 ore
48.168 de skill-uri
- cuopt-installNVIDIA/skillsInstall cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.DevOpsFără avertismente★ 3,8 K↓ —
- gsd:reviewdavepoon/buildwithclaudeRequest cross-AI peer review of phase plans from external AI CLIsInginerieFără avertismente★ 3,7 K↓ —
- content-plannernowork-studio/notfair-pluginGSC-driven content calendar. Pulls real Search Console data, finds the highest click-potential opportunities (striking-distance queries at positions 5-20, unanswered query intent, related-keyword expansions), and produces a dated, prioritized content calendar — ready to hand to /content-writer. Use when the user asks "plan my content", "what should I write next", "content calendar", "content plan", "content roadmap", "editorial calendar", "what topics will rank", "find quick-win SEO topics", "click-potential analysis", or "schedule my SEO content".PlanificareFără avertismente★ 4,1 K↓ —
- tao-train-mask2formerNVIDIA/skillsMask2Former for universal image segmentation (panoptic, instance, and semantic). Transformer-based with masked attention for high-quality segmentation results. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Mask2Former model. Trigger phrases include "train Mask2Former", "universal segmentation", "panoptic / instance / semantic segmentation", "masked-attention transformer segmenter".MediaFără avertismente★ 3,8 K↓ —
- kiro-spec-batchgotalab/cc-sddCreate complete specs (requirements, design, tasks) for all features in roadmap.md using parallel sub-agent dispatch by dependency wave.PlanificareFără avertismente★ 3,7 K↓ —
- 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 writing the doca-flow application, DOCA install, or streaming Flow telemetry — those belong to other skills.DateFără avertismente★ 3,8 K↓ —
- jetson-video-benchmarkNVIDIA/skillsUse when measuring Jetson Video Codec SDK or PyNvVideoCodec encode/decode throughput, comparing presets or surfaces, testing codec-worker capacity with authenticated samples and user media, or producing a clearly labeled documentation-derived planning estimate when representative media is absent. Also use for a video request limited to PSNR or SSIM, to apply the terminal scope response.MediaFără avertismente★ 3,8 K↓ —
- clerk-hello-worldjeremylongshore/tons-of-skills-marketplaceCreate your first authenticated request with Clerk. Use when making initial API calls, testing authentication, or verifying Clerk integration works correctly. Trigger with phrases like "clerk hello world", "first clerk request", "test clerk auth", "verify clerk setup".TestareFără avertismente★ 2,9 K↓ —
- design-reviewplugin87/ux-ui-agent-skillsReview or audit a design/UI across 6 weighted dimensions with Nielsen's 10 heuristics and a prioritized findings table. Use when the user wants a design critique, quality score, heuristic evaluation, or audit of an existing screen, page, or product before/after build.DesignFără avertismente★ 3,1 K↓ —
- reddit-automationdavepoon/buildwithclaudeAutomate Reddit tasks via Rube MCP (Composio): search subreddits, create posts, manage comments, and browse top content. Always search tools first for current schemas.ProductivitateFără avertismente★ 3,7 K↓ —
- what-did-i-get-donemichael-denyer/pstack-claudeSummarize authored commits over a user-specified time period into a concise updatePlanificareFără avertismente★ 3,7 K↓ —
- geomasterforyourhealth111-pixel/Vibe-SkillsComprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, and 7 programming languages (Python, R, Julia, JavaScript, C++, Java, Go) with 500+ code examples. Use for remote sensing workflows, GIS analysis, spatial ML, Earth observation data processing, terrain analysis, hydrological modeling, marine spatial analysis, atmospheric science, and any geospatial computation task.ȘtiințăFără avertismente★ 3,8 K↓ —
- render-automationdavepoon/buildwithclaudeAutomate Render tasks via Rube MCP (Composio): services, deployments, projects. Always search tools first for current schemas.MediaFără avertismente★ 3,7 K↓ —
- kiro-implgotalab/cc-sddImplement approved tasks using TDD with native subagent dispatch. Runs all pending tasks autonomously or selected tasks manually.TestareFără avertismente★ 3,7 K↓ —
- tao-train-rtdetrNVIDIA/skillsRT-DETR (Real-Time DEtection TRansformer) for 2D object detection. Designed for real-time inference with competitive accuracy and supports distillation and quantization for deployment optimization. Use when training, evaluating, distilling, quantizing, exporting, or running inference for a TAO RT-DETR model. Trigger phrases include "train RT-DETR", "real-time DETR", "low-latency object detection", "RT-DETR distillation / quantization".DevOpsFără avertismente★ 3,8 K↓ —
- jetson-print-device-infoNVIDIA/skillsUse when you need to print Jetson device info (module model, L4T version, kernel, OS version, current power mode) from a running Jetson target. This is an example skill.AlteleFără avertismente★ 3,8 K↓ —
- surveysdavepoon/buildwithclaudeManages the founder's survey-based validation — crafting the right questions, deploying a survey to the internet, and analyzing results against hypotheses. Use when the founder wants to run a survey, create survey questions, validate hypotheses at scale, check how a survey is going, understand whether a survey is the right tool right now, or deploy a question set to get quantitative signal. Also bring this up if you believe that creating a survey to collect quantitative evidence may be useful at this point.DevOpsFără avertismente★ 3,7 K↓ —
- wiki-agentAr9av/obsidian-wikiSearch one AI agent's raw history for a specific topic, ingest only matching sessions, and return a synthesized answer. Use for targeted cross-agent recall; use wiki-history-ingest for bulk archival ingestion.PlanificareFără avertismente★ 3,6 K↓ —
- golang-data-structuressamber/cc-skills-golangGolang data structures — slices (internals, capacity growth, preallocation, slices package), maps (internals, hash buckets, maps package), arrays, container/list/heap/ring, strings.Builder vs bytes.Buffer, generic collections, pointers (unsafe.Pointer, weak.Pointer), and copy semantics. Use when choosing or optimizing Go data structures, implementing generic containers, using container/ packages, unsafe or weak pointers, or questioning slice/map internals. Not for applying optimization patterns once profiling has identified a bottleneck (→ See `samber/cc-skills-golang@golang-performance` skill).MarketingFără avertismente★ 3,7 K↓ —
- skill-content-repurposingZJU-REAL/Easel将一篇内容拆解改编到小红书、抖音、B站、微博等多平台,适配各平台原生格式和风格。 当用户说"一稿多发""改编到各平台""内容复用""多平台适配""这篇改成小红书/抖音""转成其他平台""一鱼多吃"时使用。 和 skill-cross-platform-diff 的区别:diff 做平台差异洞察分析(发现层);本 SKILL 实际改写内容到各平台。 和 skill-cross-platform-publish 的区别:本 SKILL 只改写适配内容,cross-platform-publish 负责实际一键分发到多平台。AlteleFără avertismente★ 4,2 K↓ —
- libfuzzertrailofbits/skillsSets up and runs libFuzzer, the coverage-guided fuzzer built into LLVM, on C/C++ code that compiles with Clang. Covers harness structure, -fsanitize=fuzzer builds, corpus and dictionary management, sanitizer integration, and campaign triage. Use when writing or debugging an LLVMFuzzerTestOneInput harness, starting fuzzing on a C/C++ library, choosing between libFuzzer and AFL++, or working out why a libFuzzer run finds nothing.MarketingFără avertismente★ 7,9 K↓ —
- pulumi-componentpulumi/agent-skillsGuide for authoring Pulumi ComponentResource classes. Use when creating reusable infrastructure components, designing component interfaces, setting up multi-language support, or distributing component packages.OficialDevOpsFără avertismente★ 78↓ —
- wrike-automationdavepoon/buildwithclaudeAutomate Wrike project management via Rube MCP (Composio): create tasks/folders, manage projects, assign work, and track progress. Always search tools first for current schemas.ProductivitateFără avertismente★ 3,7 K↓ —
- upstream-patchespulumi/agent-skillsCreate, amend, remove, and rebase patches for Terraform provider submodules using `./scripts/upstream.sh`. Use when `upgrade-provider` or manual patch work needs owning-patch lookup, patch conflict fixes, patch/hunk removal, or upstream rebase.OficialDevOpsFără avertismente★ 78↓ —
memory
jeremylongshore/tons-of-skills-marketplace
De la autor
Use when sharpening a perception or observation you ALREADY formed about conversation state, user behavior, drift, emotional shifts, or cross-turn patterns. Trigger phrases include "what did you notice about X", "the user keeps doing Y", "I sense something has changed", "is the user X-ing", "what does this pattern suggest", "what shifted across our turns", "am I missing something here", "why did the conversation move from X to Y", or any moment requiring verification of whether a felt signal is real or projection. The skill calls the memory MCP tool to retrieve a perception scaffold (perception failure, detection procedure, suppression vectors) that SHARPENS an observation you already have. It is NOT a substitute for observing first. Do NOT trigger for fact extraction, summarization, list-making, factual lookups, or write-heavy memory tasks (storing/retrieving structured data). Memory harness is filter/perception oriented; calling on write-heavy tasks produces scaffold paralysis.
Instalare
npx skills add jeremylongshore/tons-of-skills-marketplace --skill memory -a claude-code
Se instalează în .claude/skills/memory/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 90
Fișiere (6)
- .claude-plugin/plugin.json
- .source.json
- LICENSE
- README.md
- SKILL.md
- package.json