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.
46.700 de skill-uri din 2.243 de depozite · actualizat acum 12 ore
46.700 de skill-uri
- tao-convert-dataset-formatNVIDIA/skillsRun `tao-daft convert` to convert NVIDIA TAO DAFT datasets between supported formats. Do not use for non-DAFT data. Use when the user asks to convert a DAFT dataset, change DAFT format, change a TAO dataset format, or run `tao-daft convert`.AlteleFără avertismente★ 3,8 K↓ —
- gsd:discuss-phasedavepoon/buildwithclaudeGather phase context through adaptive questioning before planning. Use --all to skip area selection and discuss all gray areas interactively. Use --auto to skip interactive questions (Claude picks recommended defaults). Use --chain for interactive discuss followed by automatic plan+execute. Use --power for bulk question generation into a file-based UI (answer at your own pace).DesignFără avertismente★ 3,7 K↓ —
- 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★ 3,8 K↓ —
- hubspot-automationdavepoon/buildwithclaudeAutomate HubSpot CRM operations (contacts, companies, deals, tickets, properties) via Rube MCP using Composio integration.AlteleFără avertismente★ 3,7 K↓ —
- 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★ 3,8 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★ 3,8 K↓ —
- code-formatterjeremylongshore/tons-of-skills-marketplaceExecute automatically formats and validates code files using Prettier and other formatting tools. Use when users mention "format my code", "fix formatting", "apply code style", "check formatting", "make code consistent", or "clean up code formatting". Handles JavaScript, TypeScript, JSON, CSS, Markdown, and many other file types. Trigger with relevant phrases based on skill purpose.InginerieFără avertismente★ 2,9 K↓ —
- tao-train-grounding-dinoNVIDIA/skillsGrounding DINO for open-set object detection. Combines DINO-style detection with a BERT text encoder for language-guided detection — detects objects described by text prompts without a fixed class vocabulary. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Grounding DINO model. Trigger phrases include "train Grounding DINO", "open-vocabulary detection", "text-prompted detector", "language-guided object detection".AlteleFără avertismente★ 3,8 K↓ —
- tracedocsdavepoon/buildwithclaudeTurn any codebase into evidence-grounded Markdown docs plus a machine-readable index.json. Every claim cites its source; never invents deployment steps.DevOpsFără avertismente★ 3,7 K↓ —
- narrative-drift-monitoraaron-he-zhu/aaron-marketing-skillsUse when the user asks to "check if our surfaces have drifted from the canon", "watch for competitor repositioning", or "define when we should reposition"; produces a drift report — self-drift per flagship surface vs the narrative-registry canon over time (via wayback.py, change history Measured with as-of dates), competitor-repositioning alerts, an explicit repositioning-trigger condition set, and a D1/W1/M1 message-shift retro (intended vs actual pull-through, evidence-labeled) — feeding the TALE L drift-audit sub-items and the narrative-whiplash guardrail fact base. Not for the first-time consistency check before a surface ships — use narrative-cascade-planner; not for computing the TALE profile result or running the vetoes — use narrative-quality-auditor; not for echo-rate / AI-answer resonance measurement — use narrative-resonance-monitor. 自漂移监测/竞品重定位告警/重定位触发/叙事漂移复盘PlanificareFără avertismente★ 3 K↓ —
- tao-finetune-cosmos-embedNVIDIA/skillsCosmos-Embed1 video-text embedding for text-to-video retrieval, video-to-video search, semantic deduplication, and fine-tuning. Use when the user asks to "fine-tune Cosmos-Embed1", "run cosmos-embed inference", "export Cosmos-Embed1", "embed videos", or "search videos with text".MediaFără avertismente★ 3,8 K↓ —
- creator-content-auditoraaron-he-zhu/aaron-marketing-skillsUse when the user asks to "review this influencer content" or "check if this post meets brand guidelines"; runs the typed STAR pre-publish gate, scores Trust and Appeal on the deliverable, folds in the creator Suitability read, computes the profile-weighted SQS, checks the disclosure/claim/brand-safety and fraud/fake-engagement vetoes, and writes constructive revision feedback. Not for drafting the brief — use brief-generator; not for partnership terms — use contract-helper. 达人内容审核/发布前质检JuridicFără avertismente★ 3 K↓ —
- scvi-toolsanthropics/knowledge-work-pluginsDeep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping with scANVI/scArches, (7) RNA velocity with veloVI, or (8) any deep learning-based single-cell method. Triggers include mentions of scVI, scANVI, totalVI, PeakVI, MultiVI, DestVI, veloVI, sysVI, scArches, variational autoencoder, VAE, batch correction, data integration, multi-modal, CITE-seq, multiome, reference mapping, latent space.OficialAlteleFără avertismente★ 33,4 K↓ —
- ops-firesdavepoon/buildwithclaudeProduction incidents dashboard. Reads ECS health, Sentry errors, CI failures. Offers to dispatch fix agents for active fires.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★ 3,8 K↓ —
- tao-train-mask-auto-labelNVIDIA/skillsMAL (Mask Auto-Label) for weakly-supervised segmentation. Produces segmentation masks from minimal annotations (point or box annotations) using a ViT-MAE backbone. Use when training, evaluating, or running inference for a TAO MAL model. Trigger phrases include "train MAL", "Mask Auto-Label", "weakly-supervised segmentation", "box-prompted segmentation", "minimal-annotation mask prediction".AlteleFără avertismente★ 3,8 K↓ —
- tao-list-capabilitiesNVIDIA/skillsAnswer what the TAO Skill Bank plugin can do by generating the response from packaged application, data, model, AutoML, and platform manifests. Use when the user asks "what can TAO Skill Bank do", "list TAO models", "which TAO workflows are available", or "what supports AutoML".AlteleFără avertismente★ 3,8 K↓ —
- tao-generate-anomaliesNVIDIA/skillsFull PAIDF AnomalyGen pipeline — fine-tune on a new anomaly dataset, generate synthetic anomaly images (SDG), evaluate quality (nn_score), and search per-sample (guidance, crop_ratio) parameters. Three modes: full (Phase 0→7: finetune then generate), finetune_only (Phase 0→1: train only), inference_only (Phase 0, 2→7: generate from an existing checkpoint). Use when the user asks to "fine-tune AnomalyGen", "generate anomaly images", "run PAIDF SDG", "evaluate SDG output quality", "run per-sample search", or run any part of the AnomalyGen pipeline, even if they only mention one phase.AlteleFără avertismente★ 3,8 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↓ —
- 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★ 3,8 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↓ —
- nemo-mbridge-resiliencyNVIDIA/skillsResiliency features in Megatron Bridge including fault tolerance, straggler detection, in-process restart, preemption, and re-run state machine.AlteleFără avertismente★ 3,8 K↓ —
- nemo-rl-brev-etiquetteNVIDIA/skillsBrev instance operating guidance for NeMo-RL agents working in /home/ubuntu/RL with limited workspace disk, a larger /ephemeral volume, and optional /home/ubuntu/RL/.env secrets. Use when running nemo-rl-auto-research campaigns, experiments, training jobs, model or dataset downloads, shared cache-heavy commands, log-producing runs, checkpoint generation, W&B or Hugging Face authenticated workflows, or any workflow that may create large files on Brev.ȘtiințăFără avertismente★ 3,8 K↓ —
- jetson-video-pipelineNVIDIA/skillsUse when planning, executing, and independently validating Jetson Video Codec SDK or PyNvVideoCodec encode/decode, transcode, segmentation, container decode, AV1, or concise acceptance workflows.MediaFără avertismente★ 3,8 K↓ —
cargo-fuzz
trailofbits/skills
RedactareActualizat acum 4 zile
De la autor
Sets up and runs cargo-fuzz, the standard fuzzing tool for Cargo-based Rust projects. Covers cargo fuzz init, the nightly toolchain requirement, fuzz_target! harnesses, Arbitrary-derived structured inputs, sanitizer options, cargo fuzz coverage, and reproducing a crash artifact. Use when fuzzing a Rust crate, writing a fuzz_target!, exercising unsafe blocks or FFI in Rust, or triaging a cargo fuzz crash.
Instalare
npx skills add trailofbits/skills --skill cargo-fuzz -a claude-code
Se instalează în .claude/skills/cargo-fuzz/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (CC-BY-SA-4.0) nu ne permite să-i redistribuim fișierele. Comenzile de instalare le iau direct de pe GitHub.
La ce are acces
Doar instrucțiuniFolosește rețeauaLicență: CC-BY-SA-4.0
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- SKILL.md
- agents/openai.yaml
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