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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.
47.966 de skill-uri din 2.309 depozite · actualizat acum 2 ore
47.966 de skill-uri
- linear-rate-limitsjeremylongshore/tons-of-skills-marketplaceImplement Linear request, endpoint, and GraphQL complexity budgets with reset-aware throttling. Use when coordinating workers or recovering from RATELIMITED errors. Trigger with "handle Linear rate limits", "budget Linear complexity", or "throttle Linear workers".AlteleFără avertismente★ 2,9 K↓ —
- codonfm-setupNVIDIA/skillsSet up the public CodonFM v1 repository and download public Encodon checkpoints. Use for requests to build or launch the CodonFM development container, configure local data/checkpoint mounts, verify GPU access, or download public Encodon 80M, 600M, 1B, or Cdwt-1B weights. Do not use for Decodon, Encodon 5B/10B, missense-aggregation, or codon-optimization setup because those implementations are not in the public repository.AlteleFără avertismente★ 3,8 K↓ —
- campaign-architectaaron-he-zhu/aaron-marketing-skillsUse when the user asks to "plan my paid account structure", "pick Search vs PMax", "lay out ad groups / asset groups", or "audit paid-vs-organic cannibalization"; designs campaign-type selection, ad-group/asset-group layout, targeting + match types, negative/exclusion hygiene, and a paid↔organic overlap audit, and scores the ROAS A (Audience) dimension + structure. Not for computing the final RQS — use ad-account-auditor; not for budget split — use budget-optimizer; not for organic site architecture — use site-structure-optimizer. 付费广告账户结构/广告系列规划/否定关键词MarketingFără avertismente★ 3 K↓ —
- nemo-rl-auto-researchNVIDIA/skillsAutonomous NeMo-RL research agent workflow for directed hypothesis testing and open-ended discovery. Guides agents through the full experiment lifecycle: understanding recipes and environments, wiring RL or NeMo-gym runs, launching reproducible baselines and iterations, analyzing results, preserving human oversight, and using git plus TSV logs as the research ledger. Do NOT use for: bug fixes, code review, documentation, refactoring, dependency updates, or single-file changes.ȘtiințăFără avertismente★ 3,8 K↓ —
- tao-train-nvdinov2NVIDIA/skillsNVDINOv2 for self-supervised visual representation learning. Trains vision transformers via self-distillation (teacher-student) without labels and produces general-purpose visual features. Use when training, exporting, or running inference for a TAO NVDINOv2 backbone. Trigger phrases include "train NVDINOv2", "self-supervised ViT pretraining", "DINOv2 backbone", "visual representation learning".AlteleFără avertismente★ 3,8 K↓ —
- nemo-fabric-integrateNVIDIA/skillsUse this skill when integrating NVIDIA NeMo Fabric into a consumer application, service, evaluation harness, or platform through the typed Python SDK — translating the consumer's own application, job, or deployment config into an in-memory FabricConfig, choosing the single-invocation convenience API or an explicitly started runtime, validating with plan and doctor, and consuming normalized results, artifacts, and telemetry.DevOpsFără avertismente★ 3,8 K↓ —
- kiro-verify-completiongotalab/cc-sddVerify completion and success claims with fresh evidence. Use before claiming a task is complete, a fix works, tests pass, or a feature is ready for GO.TestareFără avertismente★ 3,7 K↓ —
- golang-google-wiresamber/cc-skills-golangCompile-time dependency injection in Golang using google/wire — wire.NewSet, wire.Build, wire.Bind (interface→concrete), wire.Struct, wire.Value, wire.InterfaceValue, wire.FieldsOf, cleanup functions, //go:build wireinject injector files, and generated wire_gen.go. Apply when using or adopting google/wire, when the codebase imports `github.com/google/wire`, or when wiring an application graph at compile time via `wire.Build`. For runtime DI with reflection, see `samber/cc-skills-golang@golang-uber-dig` skill.DesignFără avertismente★ 3,7 K↓ —
- doca-compressNVIDIA/skillsHardware compression offload with DOCA Compress on a BlueField DPU, ConnectX NIC, or host: DEFLATE compress and decompress, plus LZ4 decompress (stream and block; LZ4 encode is NOT supported), instead of CPU zlib / zstd. Trigger on "offload this gzip", "decompress incoming network data on the NIC", "compress task returns INVALID_VALUE on alloc_init", "submitted a task but no completion arrives", or "decompress LZ4 on the BlueField", even without naming DOCA Compress. Covers enabling compress-deflate, decompress-deflate, decompress-lz4-stream and decompress-lz4-block tasks on a doca_compress context, sizing source / destination doca_buf against the per-task cap query, mmap permissions, offload vs CPU decisions, a round-trip smoke, and DOCA_ERROR_* from Compress calls. Refuse and route elsewhere for zstd / Snappy / brotli, LZ4 encode (a CPU LZ4 library), pure mmap-to-mmap copies (doca-dma), or DOCA Core lifecycle internals.ProductivitateFără avertismente★ 3,8 K↓ —
- trend-spotteraaron-he-zhu/aaron-marketing-skillsUse when the user asks to "find trending topics", "what trends should my brand jump on", or "time a campaign around a cultural moment"; produces a ranked trend report with brand-fit scores, format calls (rising/peak/declining), a cultural calendar, and go/skip recommendations. Not for finding the creators to run those trends — use influencer-discovery; not for building the brand posting calendar from a go verdict — use social-calendar-builder. 热点趋势洞察/借势营销MarketingFără avertismente★ 3 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★ 3,8 K↓ —
- doca-dpaNVIDIA/skillsUse this skill when the user is doing hands-on DOCA DPA host-side work on a BlueField — creating the `doca_dpa` Core context, loading a DPACC-compiled DPA app image (`doca_dpa_app`), creating DPA threads, launching kernels via `doca_dpa_kernel_launch_update_*`, draining `doca_dpa_completion`, running `doca_dpa_cap_*` discovery, choosing between the DPA comm component (inter-DPA messaging) and the DPA verbs component (in-kernel RDMA), or debugging `DOCA_ERROR_*` from `doca_dpa_*`. Trigger even without "DOCA DPA" or "Data-Path Accelerator": "run compute on the DPA from my host", "DPA kernel hangs, no completion", "DOCA_ERROR_DRIVER on launch", "DOCA/DPACC version skew", or "does this BlueField expose a DPA". Route elsewhere for DPA-side kernel programming itself, DPACC compiler internals, host↔DPU messaging (doca-comch), host-side RDMA (doca-rdma), and GPU-initiated networking (doca-gpunetio).MediaFără avertismente★ 3,8 K↓ —
- doca-telemetry-exporterNVIDIA/skillsUse this skill when the user is doing hands-on DOCA Telemetry Exporter programming on a host where DOCA is installed — defining a doca_telemetry_exporter_schema and event types, creating sources, picking a publish surface (typed events / opaque events / the metrics counter-gauge-histogram API / OTLP logs / NetFlow), walking the schema-then-source lifecycle, or debugging DOCA_ERROR_* failures from the exporter API. Trigger even when the user does not explicitly mention "DOCA Telemetry Exporter" or "doca_telemetry_exporter_*" — typical implicit phrasings include "publishing counters from my DOCA app", "BAD_STATE when I report an event", "consumer/DTS sees nothing but my report succeeded", "how do I export NetFlow/IPFIX records", or "should I link the exporter or the telemetry service". Refuse and route elsewhere for the receiving DOCA Telemetry Service (DTS), plain stdout logging via doca_log, or real-time event subscription back into the app via doca-comch — those belong to other skills.InginerieFără avertismente★ 3,8 K↓ —
- foundationpose-pipelineNVIDIA/skillsAdapt BOP datasets, run the FoundationPose perception pipeline with TAO depth, and evaluate or re-score pose results. Use for dataset runs and result comparisons; environment installation belongs to foundationpose-setup.AlteleFără avertismente★ 3,8 K↓ —
- tao-run-inference-serviceNVIDIA/skillsStart, query, and stop a network-specific TAO inference microservice ({network_arch}-inference-microservice) by delegating container execution to the appropriate platform skill. Handles container image resolution, job-payload JSON construction, and the service registry. Use when the user wants to run inference on a TAO model checkpoint using a microservice container, deploy a TAO inference endpoint, or stop a running inference container.DevOpsFără avertismente★ 3,8 K↓ —
- principle-foundational-thinkingbacknotprop/pstackApply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.RedactareFără avertismente★ 3,2 K↓ —Apare și în 2 alte depozite
- paid-ads-linkedinnowork-studio/notfair-pluginAudit, diagnose, plan, and safely operate connected LinkedIn Ads accounts through the NotFair MCP, with an export-based fallback. Use for LinkedIn advertising, sponsored content, lead-generation forms, job-title or company targeting, campaign groups, creatives, conversions, lead quality, budgets, bids, or approved LinkedIn campaign changes.MarketingFără avertismente★ 4,1 K↓ —
- directions-labNoupaperclipai/paperclipScaffold a directions lab that shows shipped UI (Today) beside 2-3 design directions, with surface tabs, theme and animation toggles and the V1 MVP hover motion, registered in design-proposals Storybook. Use for a directions page or lab, or to explore design directions next to production.DesignFără avertismente★ 108,9 K↓ —
- keyword-researchaaron-he-zhu/aaron-marketing-skillsUse when the user asks to "find keywords", "挖词", or "搜什么词"; prioritizes search volume, keyword difficulty, intent, and topic clusters from provided or connected data. Not for competitor-relative coverage gaps — use content-gap-analysis. 关键词研究/内容选题ȘtiințăFără avertismente★ 3 K↓ —
- entity-registryaaron-he-zhu/aaron-marketing-skillsUse when the user asks to "optimize entity presence", reconcile an entity identity, or update canonical Knowledge Graph facts; audits and maintains machine-facing identity, sameAs, schema, disambiguation, and AI-recognition evidence through the entities registry. Not for page-level AI-citation readiness - use geo-content-optimizer; not for human-facing brand canon - use narrative-registry. 实体注册/知识图谱AlteleFără avertismente★ 3 K↓ —
- lindy-install-authjeremylongshore/tons-of-skills-marketplaceSet up a Lindy account and authenticated webhook trigger. Use when onboarding to Lindy, configuring bearer authentication for webhook triggers, or connecting Lindy agents to your application. Trigger with phrases like "install lindy", "setup lindy", "lindy auth", "configure lindy webhook", "lindy webhook secret".AlteleFără avertismente★ 2,9 K↓ —
- token-buildplugin87/ux-ui-agent-skillsSet up or run the token build pipeline. Transform the DTCG tokens/*.json (source of truth) into platform artifacts (CSS variables, Tailwind @theme, JS/TS, iOS Asset Catalog, Android, Compose) with Style Dictionary / Tokens Studio / W3C DTCG export. Use when the user wants to generate platform theme files from tokens, wire token CI, or multi-platform token output.DesignFără avertismente★ 3,1 K↓ —
- instrument-data-to-allotropeanthropics/knowledge-work-pluginsConvert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.OficialDateFără avertismente★ 34 K↓ —
- card-xiaohongshuZJU-REAL/Easel把已有卡片文案渲染为 1080×1440 小红书竖版知识卡片组,并按 card-design 选择视觉风格。当用户说“渲染/制作小红书卡片、知识卡、滑动卡片组”时使用。整套笔记策划与文案用 xhs-note-creator;横版金句卡用 card-quote。DesignFără avertismente★ 4,2 K↓ —
skill-campaign-planner
ZJU-REAL/Easel
De la autor
活动/营销策划(国内本地化):为节日营销、电商大促(618/双11/年货节)、新品发布、活动造势 制定完整方案——目标拆解、营销节奏(预热-爆发-返场)、多平台内容矩阵、互动玩法、KOL 分层、 预算分配、风险合规、效果指标。当用户说"营销方案""活动策划""大促方案""618/双11 怎么做" "节日营销""新品发布方案""造势""campaign""营销节奏""怎么搞活动"时使用。
Instalare
npx skills add ZJU-REAL/Easel --skill skill-campaign-planner -a claude-code
Se instalează în .claude/skills/skill-campaign-planner/ · 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.
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Fișiere (3)
- EASEL-META.md
- SKILL.md
- references/campaign-frameworks.md