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
44.573 de skill-uri
- jetson-print-bsp-infoNVIDIA/skillsUse when you need to print Jetson BSP info (L4T version, board configs, rootfs state) from a Linux_for_Tegra root on the host PC. This is an example skill.AlteleFără avertismente★ 3,7 K↓ —
- jetson-customize-pcieNVIDIA/skillsPer-controller PCIe enable / disable / lanes / link-speed for a Jetson Thor or Orin custom carrier via ODMDATA + kernel-DT overlay. Do NOT use for UPHY lane allocation or endpoint-mode bring-up.AlteleFără avertismente★ 3,7 K↓ —
- i4h-workflow-validateNVIDIA/skillsRun the root-level workflow runtime policy or rule-based rollouts and verify simulator success. Use for evaluation, checkpoints, or local controllers; do not use for replay or dataset annotation.ProductivitateFără avertismente★ 3,7 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★ 7,8 K↓ —
- earth2studio-discoverNVIDIA/skillsFind Earth2Studio models, data sources, and examples for a weather/climate use case. Do NOT use for writing inference code, downloading data, or installation.RedactareFără avertismente★ 3,7 K↓ —
- doca-flow-grpc-serverNVIDIA/skillsRemote control of DOCA Flow over gRPC with the shipped `doca_flow_grpc` server: program Flow pipes and entries from Python, Go, Rust or Java, or from another host, instead of linking `libdoca_flow.so`. PLAINTEXT-ONLY: the server uses `grpc::InsecureServerCredentials()` with NO TLS / mTLS / token-auth knob; transport security must come from external infrastructure (e.g. an mTLS proxy / sidecar) on a trusted segment. Trigger even without "gRPC": "program Flow rules from Python on another host", "remotely configure pipes on the BlueField", "client times out connecting to the Flow server", "where is the .proto for Flow", "UNAUTHENTICATED / FAILED_PRECONDITION on a Flow RPC". Covers bringing up, configuring, hardening and debugging the server. Route elsewhere for the underlying doca-flow C API, generic gRPC tooling (protoc, language bindings), or DOCA install / BFB bring-up.SecuritateFără avertismente★ 3,7 K↓ —
- gsd:exploredavepoon/buildwithclaudeSocratic ideation and idea routing — think through ideas before committing to plansPlanificareFără avertismente★ 3,7 K↓ —
- terraform-testhashicorp/agent-skillsComprehensive guide for writing and running Terraform tests. Use when creating test files (.tftest.hcl), writing test scenarios with run blocks, validating infrastructure behavior with assertions, mocking providers and data sources, testing module outputs and resource configurations, or troubleshooting Terraform test syntax and execution.OficialTestareFără avertismente★ 907↓ —
- tao-run-dinov3-ssl-deftNVIDIA/skillsRun iterative DINOv3 SSL DEFT data selection and retraining from an unlabeled pool, using GRIT or multi-task weakness and fixed-encoder retrieval. Use for active-learning-style DINOv3 mining, not plain pretraining/fine-tuning (tao-train-dinov3) or AOI/PAS DEFT.ProductivitateFără avertismente★ 3,7 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★ 3,7 K↓ —
- nemotron-customizeNVIDIA/skillsPlan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or Megatron-Bridge), pretraining/CPT, RL alignment (DPO/RLVR/GRPO/RLHF), BYOB/MCQ benchmarks, checkpoint conversion, ModelOpt optimization, env profiles, and evaluation of trained checkpoints or existing/hosted endpoints. Use when a request names a Nemotron step or workflow, or asks to clean, translate, train, fine-tune, align, convert, optimize, evaluate, or compose these into a pipeline. Do NOT use for frontend/dashboard/visualization work, generic ML advice, billing/access, or non-Nemotron coding tasks.DesignFără avertismente★ 3,7 K↓ —
- nemo-retriever-mcpNVIDIA/skillsUse when a task needs to search or add documents through NeMo Retriever MCP.ProductivitateFără avertismente★ 3,7 K↓ —
- nvshmem-tune-performanceNVIDIA/skillsRoute NVSHMEM tuning to data collection, remote transport, NIC-to-PE mapping, or TMA. Do not use for unrelated CUDA, NCCL, or application tuning.AlteleFără avertismente★ 3,7 K↓ —
- mcore-create-issueNVIDIA/skillsInvestigate a failing GitHub Actions run or job and create a GitHub issue for the failure.DevOpsFără avertismente★ 3,7 K↓ —
- jetson-generate-kbNVIDIA/skillsBuild a per-target knowledge-base markdown next to the active profile by walking the BSP root and source tree. Use after init-image / init-source; not for editing profile fields.MediaFără avertismente★ 3,7 K↓ —
- jetson-init-targetNVIDIA/skillsAuthor a new Jetson target-platform profile (reference_devkit + optional custom_carrier) and update the active pointer. Use to create a target; not for switching existing profiles.AlteleFără avertismente★ 3,7 K↓ —
- Agent Cost Reportthedotmack/claude-memBelievable agent cost report for any period, default the last 7 full days PT, not counting today. Measured tokens from Claude Code transcripts priced at OpenRouter list prices (ESTIMATED), measured provider spend when a sanctioned source exists, note-taker cost separate, Timing-style HTML/PDF plus report.json, line-items.csv, evidence.json.DateFără avertismente★ 103 K↓ —Apare și în 4 alte depozite
- i4h-workflow-setupNVIDIA/skillsPreflight and set up the root-level workflow runtime. Use for installation, missing component environments, or third-party failures; do not use for rollout validation.ProductivitateFără avertismente★ 3,7 K↓ —
- doca-flow-dpa-perfNVIDIA/skillsUse this skill when the user is invoking doca_flow_dpa_perf on DPA-capable hardware (ConnectX-7 minimum supported, ConnectX-8 recommended, or BlueField-3) to measure rule update / disable rates on the DPA-offloaded DOCA Flow path — picking the active / passive device split, choosing workload-shape axes (burst, queue, completion threshold, workers, hash pipe algo, PSL tables), or reading Kops/sec iteration stats and the optional self-test. Trigger even when the user does not explicitly mention "doca_flow_dpa_perf" or "DPA Provider" — typical implicit phrasings include "how fast can the DPA program path-selector entries", "baseline rule-update rate on ConnectX-8", "tool reports zero ops on my BlueField", "self-test sentinel never shows on tcpdump", or "is my BlueField-2 DPA-capable". Refuse and route elsewhere for the host / DPU-CPU Flow path (doca-flow-perf), Flow pipeline tuning (doca-flow-tune), writing doca-flow / doca-dpa applications, or DOCA install — those belong to other skills.TestareFără avertismente★ 3,7 K↓ —
- refactor-modulehashicorp/agent-skillsTransform monolithic Terraform configurations into reusable, maintainable modules following HashiCorp's module design principles and community best practices.OficialInginerieFără avertismente★ 907↓ —
- rtvi-vlm-customize-modelNVIDIA/skillsHow to swap the VLM in the VSS Alerts Blueprint — covers RTVI-VLM microservice deployment methods, all three VLM consumers (rtvi-vlm, vlm-as-verifier, vss-agent), and health checks.DevOpsFără avertismente★ 3,7 K↓ —
- doca-gpunetioNVIDIA/skillsUse this skill when the user is doing hands-on DOCA GPUNetIO programming — wiring a CUDA kernel on an NVIDIA GPU to a doca-eth queue via doca_gpu_eth_rxq / doca_gpu_eth_txq, standing up the per-CUDA-device doca_gpu context, designing the persistent CUDA kernel that drains the GPU-visible queue, running the dual capability check (DOCA cap-query plus cudaGetDeviceProperties), registering cudaMalloc pools via doca_buf_arr_create_*, or debugging DOCA_ERROR_* returns from the GPUNetIO API. Trigger even when the user does not explicitly mention "DOCA GPUNetIO" or "persistent kernel" — typical implicit phrasings include "CUDA kernel reading packets directly from the NIC", "GPU-initiated networking on BlueField", "DOCA_ERROR_DRIVER on doca_gpu_create", "nvidia_peermem not loaded", "kernel-per-packet is too slow", or "which GPU supports GPU-side packet I/O". Refuse and route elsewhere for general CUDA programming, DOCA Ethernet queue bring-up, DOCA DPA, or DOCA install — those belong to other skills.InginerieFără 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★ 3,7 K↓ —
- 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★ 3,7 K↓ —
skill-profile-manager
ZJU-REAL/Easel
AlteleActualizat ieri
De la autor
管理账号画像全生命周期：创建空白画像、编辑六维字段、更新记忆、切换、导出和对比。 当用户说“新建/编辑/更新/切换/导出/对比画像、写进画像记忆”时使用。 首次从社媒数据生成画像用 skill-profile-builder；只提炼语言风格用 skill-voice-builder；品牌首次入驻引导用 skill-brand-onboarding。
Instalare
npx skills add ZJU-REAL/Easel --skill skill-profile-manager -a claude-code
Se instalează în .claude/skills/skill-profile-manager/ · 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 (2)
- EASEL-META.md
- SKILL.md