Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
48,168 skills from 2,325 repositories · updated 9 hours ago
48,168 skills
- task-observerrebelytics/one-skill-to-rule-them-allMonitors task execution for skill improvement opportunities: logs patterns, user corrections and methodology worth preserving to the workspace, turns them into skill updates in a weekly review, and flags repeating work as new skills. Use during ANY multi-step task, agentic workflow, or work session. Also triggers in post-task feedback discussions and when the user mentions skill observations, the observation log, or skill taxonomy. Also known as "One Skill to Rule Them All" — trigger on this phrase too. IMPORTANT: invoke this skill before the FIRST tool call of any session and before writing or proposing a plan — any turn that will involve a tool call counts. This sentence is the session-start trigger and the only activation layer that survives an unreachable config file; pair it with a CLAUDE.md instruction or a session-start hook (references/environments.md). A subagent dispatched by a session already running it does not run it: it writes nothing and puts its findings in its report.ProductivityNo warnings★ 3.7K↓ —
- notion-cost-tuningjeremylongshore/tons-of-skills-marketplaceReduce Notion integration waste across requests, workers, storage, and downstream processing without inventing API pricing. Use when a workload is noisy, slow, or infrastructure-heavy. Trigger with "reduce Notion cost", "audit Notion request waste", or "tune Notion polling".ProductivityNo warnings★ 2.9K↓ —
- nemo-mbridge-resiliencyNVIDIA/skillsResiliency features in Megatron Bridge including fault tolerance, straggler detection, in-process restart, preemption, and re-run state machine.OtherNo warnings★ 3.8K↓ —
- 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".ProductivityNo warnings★ 3.8K↓ —
- gsd:helpdavepoon/buildwithclaudeShow available GSD commands and usage guideOtherNo warnings★ 3.7K↓ —
- 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".OtherNo warnings★ 3.8K↓ —
- 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".OtherNo warnings★ 3.8K↓ —
- 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.DesignNo warnings★ 3.8K↓ —
- skill-content-repurposingZJU-REAL/Easel将一篇内容拆解改编到小红书、抖音、B站、微博等多平台,适配各平台原生格式和风格。 当用户说"一稿多发""改编到各平台""内容复用""多平台适配""这篇改成小红书/抖音""转成其他平台""一鱼多吃"时使用。 和 skill-cross-platform-diff 的区别:diff 做平台差异洞察分析(发现层);本 SKILL 实际改写内容到各平台。 和 skill-cross-platform-publish 的区别:本 SKILL 只改写适配内容,cross-platform-publish 负责实际一键分发到多平台。OtherNo warnings★ 4.2K↓ —
- latex-submission-pipelineforyourhealth111-pixel/Vibe-SkillsUse when building a LaTeX manuscript submission pipeline with templates, latexmk, BibTeX/Biber, chktex, latexindent, CI PDF builds, compile debugging, and submission zip packaging.DocumentsNo warnings★ 3.8K↓ —
- doca-flow-tuneNVIDIA/skillsUse this skill when the user is tuning a live or captured `doca-flow` pipeline with `doca_flow_tune` — snapshotting pipe / counter / KPI state, picking a tuning axis (rule placement, resource hints / table sizing, HW-offload mode) and a matching measurement (rule-install rate, lookup latency, hardware-counter delta), running offline or online (read-only or state-changing) modes, reading the dumper CSV / analyze JSON / visualize mermaid, or applying a recommendation back into the Flow program. Trigger even when the user does not explicitly mention "doca_flow_tune" — typical implicit phrasings include "Flow rule-install rate is low on BlueField", "table sizing looks wrong for this pipe", "tune visualize step is empty", "before/after counters don't move", or "which doca-flow knob does this recommendation hit". Refuse and route elsewhere for writing the doca-flow application, DOCA install, or streaming Flow telemetry — those belong to other skills.DataNo warnings★ 3.8K↓ —
- tao-train-pointpillarsNVIDIA/skillsPointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D detection — used in autonomous driving and robotics. Use when training, evaluating, exporting, pruning, retraining, or running inference for a TAO PointPillars model. Trigger phrases include "train PointPillars", "LiDAR 3D detection", "point-cloud object detection", "pillar-based 3D detector".MediaNo warnings★ 3.8K↓ —
- 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.MediaNo warnings★ 3.8K↓ —
- governanceplugin87/ux-ui-agent-skillsGovern how the design system evolves (SemVer for tokens/components, the contribution workflow, deprecation policy, and change communication). Use when the user wants to add/promote/deprecate a component or token, decide a version bump, set up a contribution process, or keep the system from fragmenting.DesignNo warnings★ 3.1K↓ —
- tao-train-rtdetrNVIDIA/skillsRT-DETR (Real-Time DEtection TRansformer) for 2D object detection. Designed for real-time inference with competitive accuracy and supports distillation and quantization for deployment optimization. Use when training, evaluating, distilling, quantizing, exporting, or running inference for a TAO RT-DETR model. Trigger phrases include "train RT-DETR", "real-time DETR", "low-latency object detection", "RT-DETR distillation / quantization".DevOpsNo warnings★ 3.8K↓ —
- kiro-debuggotalab/cc-sddInvestigate implementation failures using root-cause-first debugging. Use when an implementer is blocked, verification fails, or repeated remediation does not converge.EngineeringNo warnings★ 3.7K↓ —Also in 7 other repos
- kiro-spec-requirementsgotalab/cc-sddGenerate EARS-format requirements based on project description and steering context. Use when generating requirements from project description.PlanningNo warnings★ 3.7K↓ —
- kiro-validate-designgotalab/cc-sddInteractive technical design quality review and validation. Use when reviewing design before implementation.DesignNo warnings★ 3.7K↓ —
- 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).SecurityNo warnings★ 3.7K↓ —
- kiro-spec-batchgotalab/cc-sddCreate complete specs (requirements, design, tasks) for all features in roadmap.md using parallel sub-agent dispatch by dependency wave.PlanningNo warnings★ 3.7K↓ —
- kiro-discoverygotalab/cc-sddEntry point for new work. Determines the best action path or work decomposition (update existing spec, create new spec, mixed decomposition, or no spec needed) and refines ideas through structured dialogue.PlanningNo warnings★ 3.7K↓ —
- kiro-spec-designgotalab/cc-sddCreate comprehensive technical design for a specificationDesignNo warnings★ 3.7K↓ —
- kiro-spec-initgotalab/cc-sddInitialize a new specification with detailed project descriptionPlanningNo warnings★ 3.7K↓ —
- gsd:ai-integration-phasedavepoon/buildwithclaudeGenerate AI design contract (AI-SPEC.md) for phases that involve building AI systems — framework selection, implementation guidance from official docs, and evaluation strategyDesignNo warnings★ 3.7K↓ —
video-highlights
ZJU-REAL/Easel
From the author
长视频 / 直播录像高光切片:从一条长视频里找出高光片段,切成多条独立短视频,可选转竖版 9:16 + 加字幕。找点两种方式——音频能量峰值(情绪高涨/欢呼/大声处)或转录后由内容判断挑金句段。当用户说 直播切片、高光切片、长视频切短、录像剪精华、切片、高光时刻、把直播剪成短视频、提取精彩片段、长视频找亮点 时使用。基于 shared/scripts/highlight_cut.py(librosa 能量分析)。与 clipify 区别:clipify 专做英文口播找笑点+动态人脸pan,本 SKILL 更通用(中文/直播皆可)、静态转竖版更稳。
Install
npx skills add ZJU-REAL/Easel --skill video-highlights -a claude-code
Installs to .claude/skills/video-highlights/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Safety checks on SKILL.md
No warnings.
Why 90
Files (1)
- SKILL.md