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.
47.307 skill-uri din 2.272 de depozite · actualizat acum 3 ore
46.198 de skill-uri
- pulumi-upgrade-providerpulumi/agent-skillsAutomate Pulumi provider repo upgrades with the `upgrade-provider` tool. Use when upgrading a pulumi provider repository to a new upstream version, running `upgrade-provider`, and addressing its common failure modes like patch conflicts or missing module mappings.OficialAlteleFără avertismente★ 78↓ —
- writing-lean-proofstrailofbits/skillsWrites and reviews structured Lean 4 proofs and designs Lean libraries following Mathlib conventions. Use when proving theorems in Lean, formalizing mathematics or specifications in Lean 4, defining new types or definitions in a Lean library, reviewing Lean proofs for readability and maintainability, refactoring long tactic proofs into lemmas, filling in sorry placeholders in a Lean development, setting up CI or linters for a Lean project, diagnosing slow proofs or maxHeartbeats timeouts, or writing custom tactics, macros, or linters.RedactareFără avertismente★ 7,9 K↓ —
- create-planforyourhealth111-pixel/Vibe-SkillsCreate a concise plan. Use when a user explicitly asks for a plan related to a coding task.PlanificareFără avertismente★ 3,8 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
- agent-patternsjeremylongshore/tons-of-skills-marketplaceExecute this skill should be used when the user asks about "SPAWN REQUEST format", "agent reports", "agent coordination", "parallel agents", "report format", "agent communication", or needs to understand how agents coordinate within the sprint system. Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.ProductivitateFără avertismente★ 2,9 K↓ —
- adobe-observabilityjeremylongshore/tons-of-skills-marketplaceInstrument Adobe integrations with redacted structured logs, request/job/activation correlation, service-level indicators, alerts, and evidence retention. Use when the task requires adobe content-safe observability. Trigger with "monitor Adobe API", "Adobe observability", or "App Builder logs".DevOpsFără avertismente★ 2,9 K↓ —
- klingai-team-setupjeremylongshore/tons-of-skills-marketplaceConfigure Kling AI for teams with per-project API keys, usage quotas, and role-based access. Trigger with phrases like 'klingai team', 'kling ai organization', 'klingai multi-user', 'shared klingai access'.InginerieFără avertismente★ 2,9 K↓ —
- tao-train-single-stepNVIDIA/skillsStandard single-step train/eval/export workflow for any TAO model. Use when training a TAO model on a dataset without iterative data augmentation, AutoML, or DEFT loops. Trigger phrases include "single train run", "train then evaluate then export", "plain TAO training", "normal training", "no AutoML", "skip the loop". Routes through the per-model SKILL.md for action specifics and through `tao-launch-workflow` for platform/credentials/dataset intake.PlanificareFără avertismente★ 3,8 K↓ —
- ultracostdavepoon/buildwithclaudeQuality-first per-stage model routing AND a pre-flight cost gate for Claude Code dynamic workflows. Use when authoring or running ultracode / dynamic-workflow scripts, spawning subagents, or writing agent() stages — pin the right model and effort on every stage, then estimate cost and confirm with the user before launching. Verify scripts with /ultracost:check.RedactareFără avertismente★ 3,7 K↓ —
- kermt-monitorNVIDIA/skillsCheck progress for a detached KERMT run (pretrain, finetune, or any kermt_run_detached invocation). Reads run.json, queries docker for container state, tails the pretrain/finetune log, and parses progress lines (epoch, step, val loss).DevOpsFără avertismente★ 3,8 K↓ —
- doca-container-deploymentNVIDIA/skillsRunning an in-bundle DOCA service as a container on a BlueField (Argus, DMS, Firefly, or UROM service): kubelet standalone watching a static-pod manifests directory, YAML pod-spec drop, kubelet status / ENTRYPOINT logs / per-service liveness. Trigger on "how do I run my built service on the BlueField?", "where do I drop the pod-spec YAML?", "pod stuck in Pending / ImagePullBackOff / CrashLoopBackOff", "container Running but service isn't ready", "pod restart-loops after edit", or "DMS and Firefly together", even without naming container deployment. A DOCA-linked binary launched directly on the host or Arm belongs to doca-bare-metal-deployment. Covers smoke-before-bulk and the layered error taxonomy (pod-spec, scheduling, image pull, runtime, mount, network, version, host). Refuse and route elsewhere for per-service config schemas, DOCA install, library-API questions, external NVIDIA services (BlueMan, HBN, SNAP, Virtio-net), or full Kubernetes-cluster ops.DevOpsFără avertismente★ 3,8 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↓ —
- codonfm-scoreNVIDIA/skillsValidate, prepare, or run public CodonFM Encodon masked-codon variant scoring and review compatibility of its scoring workflows. Use only when the user explicitly requests CodonFM or Encodon, or that context is already established in the conversation. Do not select this skill for a generic variant-scoring request without that context; ask for the variant and intended analysis first.InginerieFără avertismente★ 3,8 K↓ —
- tao-launch-workflowNVIDIA/skillsThe mandatory pre-launch gate and four-verb execution contract for every TAO workflow or action. Invoke BEFORE launching anything side-effecting — AutoML, train, evaluate, inference, export, TensorRT engine generation, or DEFT/application workflows — on any execution platform. Covers platform selection, credentials, image confirmation, dataset intake, preflight, the launch review, job records, monitoring, and failure/retry classification. Trigger phrases include "train this model", "run AutoML", "launch on SLURM/docker/k8s/brev/virtualenv", "evaluate my checkpoint", "start a TAO job".ProductivitateFără avertismente★ 3,8 K↓ —
- nvshmem-get-startedNVIDIA/skillsUse when NVSHMEM beginners want a tutorial-style overview on assessment, mental models, first C/C++ or Python NVSHMEM programs, compilation, launching, and next steps.InginerieFără avertismente★ 3,8 K↓ —
- doca-urom-svcNVIDIA/skillsOperate the DOCA UROM Service container on BlueField Arm for remote memory operations (puts, gets, atomics, collectives) enqueued by a paired host using `doca-urom`: pull the NGC image, choose the UCX component, size queues, configure Comch pairing, and align host and service versions. SECURITY: the service has no standalone access control; Comch pairing and RDMA permissions are the boundary. Pair only intended hosts, expose least-privilege memory regions, and verify both views before start. Trigger for slow UCX collectives, unexpected NOT_PERMITTED, or missing completions. Do not use for host application code, MPI/UCX integration design, or DOCA install.SecuritateFără avertismente★ 3,8 K↓ —
- remotion-to-hyperframesheygen-com/hyperframesBring existing video code or footage into HyperFrames and verify it frame by frame against the original - Remotion first, also Motion Canvas, Lottie, Three.js, p5.js, canvas or plain HTML/CSS animation, or renders from Manim, After Effects or Blender. Use to port, convert, migrate or reuse work made with another tool.OficialDesignFără avertismente★ 74,4 K↓ —
- jetson-init-sourceNVIDIA/skillsSet up the BSP source workspace: Linux_for_Tegra overlay tracker, bsp_sources, Crosstool-NG toolchain. Use after jetson-init-image; not for fetching inputs.MediaFără avertismente★ 3,8 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★ 3,8 K↓ —
- doca-rdmaNVIDIA/skillsRDMA data movement on NVIDIA BlueField/ConnectX NICs (RoCE/InfiniBand) with DOCA RDMA, instead of hand-written libibverbs/rdma_cm. Use when the user moves data between processes or hosts over the NIC, or hits "one-sided read returns permission denied", "completions never arrive after submit", "connection callback never fires", atomic compare-and-swap over RoCE, or DOCA_ERROR_FULL on the send queue under burst, even without naming DOCA RDMA. Covers bringing up an RDMA context on a doca_dev, connection methods (RDMA CM, bridge/OOB, or gRPC exchange of doca_rdma_export()), the eleven task types (Send/Receive/Send-Imm, Read/Write/Write-Imm, Atomic CmpSwap/FetchAdd, Get/Set/Add Remote Sync Event), matching mmap + RDMA permissions, queue and connection sizing, doca_rdma_cap_* queries, and DOCA_ERROR_* from RDMA calls. Raw QP/verbs control belongs to doca-verbs. Refuse and route elsewhere for general RDMA / ibverbs theory (queue pairs, MRs, RoCE vs IB), installing DOCA itself, or non-RDMA DOCA libraries.RedactareFără avertismente★ 3,8 K↓ —
- doca-argpNVIDIA/skillsUse this skill for hands-on DOCA Arg Parser CLI work on a shipped sample or new DOCA-using app — adding / removing / renaming flags; wiring `doca_argp_init` → register params → `doca_argp_start` → `doca_argp_destroy` in order; picking a parameter type from the full public enum (`DOCA_ARGP_TYPE_STRING`, `_INT`, `_BOOLEAN`, `_DEVICE`, `_DEVICE_REP`, `_DOUBLE` — six values, not three); preserving the built-in DOCA flags (`-h` `-v` `-l` `--sdk-log-level` `--log-filter` `-j`/`--json`, NOT `--json-config`); `--device` is per-program; or debugging `DOCA_ERROR_BAD_STATE` / `INVALID_VALUE` / `NOT_SUPPORTED` / `IO_FAILED` from `doca_argp_*`. Trigger on implicit phrasings: "add a custom flag to a DOCA sample", "should I use getopt here", "BAD_STATE registering a new param", "my JSON config key is rejected", or "my sample's --json is ignored". Refuse and route elsewhere for variadic-flag / subcommand / shell-completion features, DOCA Core context, or DOCA Log internals.InginerieFără avertismente★ 3,8 K↓ —
- rag-perfNVIDIA/skillsPerformance benchmarking for a deployed NVIDIA RAG Blueprint server: profiling pass + aiperf load test driven by a single YAML config. Not for accuracy / RAGAS scoring (use rag-eval) or for deploying / repairing services (use rag-blueprint).TestareFără avertismente★ 3,8 K↓ —
- tao-train-codetrNVIDIA/skillsCo-DETR (CoDINO) for object detection. A DETR-family detector with collaborative hybrid assignment — auxiliary one-to-many heads supervise the encoder during training, giving strong closed-set accuracy at high inference cost. Use when training, evaluating, or running inference for a TAO Co-DETR model. Trigger phrases include "train Co-DETR", "run CoDINO", "codetr inference", "collaborative DETR", "autolabel detections with Co-DETR".AlteleFără avertismente★ 3,8 K↓ —
- tao-run-on-slurmNVIDIA/skillsRemote SLURM GPU cluster execution over SSH with sbatch/srun, Pyxis/Enroot containers, and Lustre-backed results. Use when running TAO training/eval/inference jobs on an on-prem or DGX SLURM cluster. Trigger phrases include "run on SLURM", "submit sbatch", "DGX SLURM cluster", "Pyxis/Enroot container", "Lustre dataset".AlteleFără avertismente★ 3,8 K↓ —
fp-check
trailofbits/skills
SecuritateActualizat acum 21 de ore
De la autor
Systematically verifies suspected security bugs to eliminate false positives, producing a TRUE POSITIVE or FALSE POSITIVE verdict with documented evidence for each. Use when asked whether a specific finding is real, exploitable, or a false positive, or to verify or validate a suspected vulnerability — not for hunting or discovering new bugs.
Instalare
npx skills add trailofbits/skills --skill fp-check -a claude-code
Se instalează în .claude/skills/fp-check/ · 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 instrucțiuniNu am văzut acces la rețeaLicență: CC-BY-SA-4.0
Verificări de siguranță pe SKILL.md
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De ce 90
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Proveniență87
Întreținere100
Licență80
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Fișiere (9)
- SKILL.md
- agents/openai.yaml
- assets/trail-of-bits-mark.svg
- references/bug-class-verification.md
- references/deep-verification.md
- references/evidence-templates.md
- references/false-positive-patterns.md
- references/gate-reviews.md
- references/standard-verification.md