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 10 ore
46.700 de skill-uri
- kiro-spec-quickgotalab/cc-sddQuick spec generation with interactive or automatic modePlanificareFără avertismente★ 3,7 K↓ —
- exploitsdavepoon/buildwithclaudeAnalyze exploit intelligence for a vulnerability against the current repositorySecuritateFără avertismente★ 3,7 K↓ —
- ulw-researchcode-yeongyu/oh-my-openagentRuns maximum-saturation research with a cooperating team, claim-graph gating, and a cited, QA'd deliverable. Use when the user explicitly asks for research or a deep investigation, including any 'ulw' research wording.ȘtiințăFără avertismente★ 70,4 K↓ —
- ulw-loopcode-yeongyu/oh-my-openagentA goal-like loop that decomposes work into systematic, evidence-bound ultrawork steps. Use when the user wants a goal loop or durable, checkpointed execution.AlteleFără avertismente★ 70,4 K↓ —
- tycanadavepoon/buildwithclaudePersistent task management and productivity intelligence via MCP. Captures tasks from conversation, plans your day, tracks patterns, and gives personalized recommendations that improve over time.PlanificareFără avertismente★ 3,7 K↓ —
- gsd:secure-phasedavepoon/buildwithclaudeRetroactively verify threat mitigations for a completed phaseAlteleFără avertismente★ 3,7 K↓ —
- gsd:remove-phasedavepoon/buildwithclaudeRemove a future phase from roadmap and renumber subsequent phasesPlanificareFără avertismente★ 3,7 K↓ —
- gsd:profile-userdavepoon/buildwithclaudeGenerate developer behavioral profile and create Claude-discoverable artifactsAlteleFără avertismente★ 3,7 K↓ —
- gsd:map-codebasedavepoon/buildwithclaudeAnalyze codebase with parallel mapper agents to produce .planning/codebase/ documentsPlanificareFără avertismente★ 3,7 K↓ —
- mass-ulwcode-yeongyu/oh-my-openagentDrives dependency-ordered child work through the native workflow tool, each phase's stages defined up front in one run, with retry/amend/send recovery. Use when the user asks for mass-ulw, a DAG of tasks, or fan-out work where some tasks must wait on others.ProductivitateFără avertismente★ 70,4 K↓ —
- gsd:join-discorddavepoon/buildwithclaudeJoin the GSD Discord communityAlteleFără avertismente★ 3,7 K↓ —
- denarioforyourhealth111-pixel/Vibe-SkillsMultiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.DateFără avertismente★ 3,8 K↓ —Apare și în 2 alte depozite
- physicsnemo-shard-tensorNVIDIA/skillsOfficial NVIDIA-authored guidance for PhysicsNeMo ShardTensor domain parallelism — integrate domain parallelism into training/inference scripts (new or existing) with DDP or FSDP2, write and register shard patches to enable new layers/ops, and bootstrap multi-GPU correctness tests. Use when working with ShardTensor, scatter_tensor, domain parallelism, sequence/spatial sharding, ring attention, DeviceMesh + DDP/FSDP2 hybrid parallelism, or physicsnemo.domain_parallel. Do NOT use for generic PyTorch DDP/FSDP setup without domain parallelism, picking a PhysicsNeMo model or example (use physicsnemo-discover), or non-distributed training questions.TestareFără avertismente★ 3,8 K↓ —
- principle-outcome-oriented-executionmichael-denyer/pstack-claudeApply during planned rewrites and migrations with explicit phase boundaries. Converge on the target architecture; don't preserve smooth intermediate states with throwaway compatibility code.PlanificareFără avertismente★ 3,5 K↓ —
- kiro-spec-statusgotalab/cc-sddShow specification status and progressPlanificareFără avertismente★ 3,7 K↓ —
- principle-guard-the-context-windowmichael-denyer/pstack-claudeApply when context is filling up: large outputs, long files, repeated reads, fan-out planning. Route bulk to subagents; keep summaries in the main thread, not raw payloads.ProductivitateFără avertismente★ 3,5 K↓ —
- correctmichael-denyer/pstack-claudeFind the mistakes agents keep repeating in this repo and make each one impossible. Try architecture first, then types, then a lint whose error names the fix, then a test, and write docs last. Prove each check fails on a real past mistake. Repeat this each time the operator corrects you. Use for /correct.TestareFără avertismente★ 3,5 K↓ —
- babysitmichael-denyer/pstack-claudeWatch an open PR — fix failing CI, handle the straightforward review comments, and drive it to a mergeable state. Claude Code analog of Cursor's built-in /babysit. Use after opening a PR when the user wants the agent to shepherd it without re-prompting.InginerieFără avertismente★ 3,5 K↓ —
- run-acceptance-testshashicorp/agent-skillsGuide for running acceptance tests for a Terraform provider. Use this when asked to run an acceptance test or to run a test with the prefix `TestAcc`, when a test fails with missing environment variables, or when diagnosing a failing or suspiciously passing acceptance test.OficialTestareFără avertismente★ 910↓ —
- principle-boundary-disciplinemichael-denyer/pstack-claudeApply when wiring validation, error handling, or framework adapters. Concentrate guards at system boundaries (CLI, config, network, external APIs); trust internal types and keep business logic in pure functions.InginerieFără avertismente★ 3,5 K↓ —
- runway-hello-worldjeremylongshore/tons-of-skills-marketplaceCreate, observe, and preserve one approved Runway text-to-video task using the current per-model contract. Use when proving the first billable generation path. Trigger with: "Runway hello world", "first Runway video", "smoke test Runway generation".TestareFără avertismente★ 2,9 K↓ —
- kiro-spec-requirementsgotalab/cc-sddGenerate comprehensive requirements for a specificationPlanificareFără avertismente★ 3,7 K↓ —
- golang-dependency-managementsamber/cc-skills-golangDependency management for Golang projects — go.mod and go.sum, `go get` install and upgrade flows, Minimal Version Selection, conflict resolution with replace/exclude/retract, `govulncheck` scanning of the module tree, outdated dependency and binary size auditing, vendoring, `tool` directives, and go.work workspaces. Use when adding, removing, or upgrading Go dependencies, deciding whether to take on a package, resolving version conflicts, or auditing what a module pulls in. Covers choosing and upgrading dependency versions, not the surrounding tooling: do NOT use for fixing an exploitable vulnerability in code (→ See `samber/cc-skills-golang@golang-security` skill) or for wiring Dependabot/Renovate update bots into CI workflows (→ See `samber/cc-skills-golang@golang-continuous-integration` skill).SecuritateFără avertismente★ 3,7 K↓ —
- golang-how-tosamber/cc-skills-golangGolang skills orchestrator — always active on any Golang coding, review, debug, or setup task. Reads the task context and loads the most relevant skills from samber/cc-skills-golang, often multiple at once: writing a gRPC service loads golang-grpc + golang-testing + golang-error-handling; debugging a panic loads golang-troubleshooting + golang-safety; auditing security loads golang-security + golang-lint + golang-safety. Also: disambiguates competing clusters when two skills seem to overlap (performance vs benchmark vs troubleshooting, samber/lo vs mo vs ro, DI cluster, safety vs security), and configures the project's agent-config file (CLAUDE.md, AGENTS.md, GEMINI.md, Cursor rules, or Copilot instructions) to force-trigger skills in a project (/golang-how-to configure).SecuritateFără avertismente★ 3,7 K↓ —
tao-finetune-clip
NVIDIA/skills
DevOpsActualizat ieri
De la autor
CLIP vision-language model for image-text retrieval, zero-shot classification, embedding extraction, ONNX export, and TensorRT deployment. Use when fine-tuning or training CLIP, running zero-shot classification, computing image embeddings, or deploying CLIP to ONNX/TensorRT. This is a single-action model skill; do not use it for an iterative weak-attribute improvement loop that keeps retraining and evaluating until progress stops, which belongs to tao-run-deft-pas.
Instalare
npx skills add NVIDIA/skills --skill tao-finetune-clip -a claude-code
Se instalează în .claude/skills/tao-finetune-clip/ · 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 (23)
- BENCHMARK.md
- SKILL.md
- config/skillspector-baseline.yaml
- evals/evals.json
- references/clip-peft.md
- references/error-patterns.md
- references/pas-metrics.md
- references/skill_info.yaml
- references/spec-param-inference.md
- references/spec_template.yaml
- references/spec_template_deploy.yaml
- references/spec_template_evaluate.yaml
- încă 11