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.
13,741 skills from 402 repositories · updated 11 minutes ago
1,054 skills
- tablebrycewang-stanford/Auto-Empirical-Research-SkillsEconometrics skill for creating publication-quality LaTeX regression and summary tables. Activates when the user asks about: "regression table", "LaTeX table", "esttab", "stargazer", "modelsummary", "publication table", "format results", "multi-panel table", "journal table", "export regression results", "table formatting", "回归表格", "LaTeX表格", "结果导出", "论文表格", "回归结果格式化", "多模型表格"ProductivityNo warnings★ 4.7K↓ —
- obsidian-basesbrycewang-stanford/Auto-Empirical-Research-SkillsCreate and edit Obsidian Bases (.base files) with views, filters, formulas, and summaries. Use when working with .base files, creating database-like views of notes, or when the user mentions Bases, table views, card views, filters, or formulas in Obsidian.ProductivityNo warnings★ 4.7K↓ —
- c5brycewang-stanford/Auto-Empirical-Research-SkillsMeta-Analysis Master with Data Integrity, Effect Size, Error Prevention & Sensitivity Multi-gate validation and workflow orchestration for meta-analysis. Absorbed C6 (Data Integrity Guard), C7 (Error Prevention Engine), B3 (Effect Size Extractor), E5 (Sensitivity Analysis - Meta) capabilities Triggers: meta-analysis, pooled effect, heterogeneity, forest plot, funnel plot, Hedges g, data integrity, effect size extraction, sensitivity analysisProductivityNo warnings★ 4.7K↓ —
- stata-logbrycewang-stanford/Auto-Empirical-Research-SkillsTail, read, or search a Stata log file from a previous command or background task.ProductivityNo warnings★ 4.7K↓ —
- workflow-schema-tuningbreaking-brake/cc-wf-studioUse when modifying `resources/workflow-schema.json` in cc-wf-studio to influence how AI agents generate workflows via the cc-workflow-ai-editor skill. Triggers include "AIが特定のノードタイプを選んでくれない", "ワークフロー生成のバイアスを調整したい", "スキーマの description を変えたい", "新しいノードタイプを追加したい", "嘘の制約がスキーマに混じっていないか確認したい". Covers what the schema actually does (instructions to AI, not runtime constraints), the design philosophy (align direction, do not prescribe rules), the build pipeline (.json → .toon auto-generated), and known bias sources to audit.ProductivityNo warnings★ 5.4K↓ —
- diverga-memorybrycewang-stanford/Auto-Empirical-Research-SkillsDiverga Memory System v7.0 - Context-persistent research support with checkpoint auto-trigger and cross-session continuity. Triggers: memory, remember, context, recall, checkpoint, decision, persist, 기억, 맥락, 세션, 체크포인트ProductivityNo warnings★ 4.7K↓ —
- next-taskbreaking-brake/cc-wf-studioRun one unattended IMPLEMENTATION iteration of the autonomous value-creation loop — steward any in-flight PR, fix interrupts (red CI / security / human bugs), or else build ONE queued `idea` issue on a branch off auto-dev and open a PR that squash-merges on green CI. Ideation lives in the next-idea skill; this skill consumes its queue. Use when the user says "次のタスク", "next task", "続きをやって", or wants autonomous progress without specifying what to do.ProductivityNo warnings★ 5.4K↓ —
- next-ideabreaking-brake/cc-wf-studioRun one unattended IDEATION iteration of the autonomous value-creation loop — invent improvements a user of cc-wf-studio would notice, judge them against the value bar, and file the winners as locked `idea` issues. Never implements anything; the next-task skill builds from the queue this skill fills. Use when the user says "アイデア出して", "next idea", or wants proposals without implementation.ProductivityNo warnings★ 5.4K↓ —
- narco-checkopen-gitagent/opengapMemory integrity audit. Detects hallucinations, circular confirmations, and state poisoning. Runs automatically after 2 consecutive failures or at nightly deep dive. Uses Opus 4.6 as the auditor model.ProductivityNo warnings★ 3K↓ —
- packet-factoryopen-gitagent/opengapCreates, reviews, and dispatches atomic work packets. Every task with a side effect requires an APPROVED packet before execution. Scope is immutable after approval — expansion requires a new packet.ProductivityNo warnings★ 3K↓ —
- tao-analyze-gaps-vlm-bcqNVIDIA/skillsExtract false-positive and false-negative gaps from VLM binary-classification-question (BCQ, yes/no) predictions. Use when the user asks to "analyze VLM BCQ gaps", "extract VLM false positives and false negatives", or identify failure cases from a predictions JSON for DEFT root-cause analysis on a binary-classification VLM workflow.ProductivityNo warnings★ 3.7K↓ —
- skill-event-calendarZJU-REAL/Easel查询未来 N 天的节日、纪念日、电商节点、行业事件，为创作者提供内容蹭点。 覆盖中国节假日、国际节日、电商大促、行业展会、考试节点、体育赛事等。 当用户说"未来有什么节日"、"下个月有什么可以蹭"、"节点日历"、"营销日历"、 "有什么热点可以提前准备"、"内容日历节点"、"最近有什么节日"、 "什么时候有大促"、"节日营销"时触发。 和 skill-content-calendar 的区别：content-calendar 排内容发布日程， event-calendar 提供节日和事件的数据查询，是选题灵感的上游数据源。ProductivityNo warnings★ 4K↓ —
- jetson-inference-mem-tuneNVIDIA/skillsPick the serving stack and per-runtime memory flags (vLLM, SGLang, llama.cpp, TensorRT Edge-LLM) for an LLM/VLM workload on any NVIDIA Jetson.ProductivityNo warnings★ 3.7K↓ —
- tao-analyze-detection-kpiNVIDIA/skillsRun TAO Data Services KPI analysis for object detection, comparing inference annotations against ground truth to compute per-class TP/FP/FN/TN, precision, recall, accuracy, and AP at a fixed IoU. Use when an object detection workflow needs per-class mAP reported after inference, or when the user asks to "run KPI analyze", "compute detection mAP", or "score my OD predictions against ground truth".ProductivityNo warnings★ 3.7K↓ —
- ctrl-clipdavepoon/buildwithclaude⧉ Copy a message to the system clipboard cleanly formatted — no blockquote pipes, no terminal bars, no Claude commentary. Use whenever you draft a message the user will paste (Slack, Teams, PR comment, email) to add a clickable "⧉ ctrl + click" copy link under it, and when the user says "/ctrl-clip", "copy that", "put it on the clipboard" (in any language). Optional argument picks the target format: slack (default), md, plain.ProductivityNo warnings★ 3.7K↓ —
- xhs-note-creatorZJU-REAL/Easel小红书内容总入口：生成标题、正文、caption、hashtags，以及 3-9 张图文卡片或短视频分镜，覆盖素材分析、卖点评估、去 AI 味和质检。 当用户说“写/做小红书笔记、小红书图文/种草/文案、出一套卡片、小红书视频”时使用。 整套笔记用本 SKILL；仅渲染卡片用 card-xiaohongshu；其他平台的通用文案用 social-content。ProductivityNo warnings★ 4K↓ —
- obsidian-markdownanbeime/skill技术写作员与内容创作者在构建Obsidian知识库时，当需要编写带双向链接、Callout或Frontmatter的复杂笔记，使用此技能可精准生成标准Markdown文档，完美支持wikilinks与嵌入，大幅提升知识管理与排版效率！ProductivityNo warnings★ 8.5K↓ —
- json-canvasanbeime/skill产品经理与内容创作者在构建Obsidian知识库或梳理复杂逻辑时，当需要创建思维导图、流程图等可视化画布，使用此技能可自动生成标准.canvas文件，精准配置节点、连线与层级，一键生成完美排版，彻底告别手写JSON的繁琐与报错。ProductivityNo warnings★ 8.5K↓ —
- context-fundamentalsforyourhealth111-pixel/Vibe-SkillsThis skill should be used when the user asks to "understand context", "explain context windows", "design agent architecture", "debug context issues", "optimize context usage", or discusses context components, attention mechanics, progressive disclosure, or context budgeting. Provides foundational understanding of context engineering for AI agent systems.ProductivityNo warnings★ 3.8K↓ —
- obsidian-basesanbeime/skill内容创作者与技术写作员在管理海量笔记时，当需要构建 Obsidian 数据库视图、配置过滤器或编写 YAML 公式，使用此技能可自动生成标准 .base 文件，轻松实现笔记的表格/卡片多维展示与数据汇总，让知识库管理效率翻倍。ProductivityNo warnings★ 8.5K↓ —
- task-decompositionrohitg00/skillkitBreaks down complex software, writing, or research tasks into small, atomic, independently completable units with dependency graphs and milestone breakdowns. Use when the user asks to plan a project, decompose a feature, create subtasks, split up work, or needs help organizing a large piece of work into a step-by-step plan. Triggered by phrases like "break down", "decompose", "where do I start", "too big", "split into tasks", "work breakdown", or "task list".ProductivityNo warnings★ 1.6K↓ —
- explaining-machine-learning-modelsforyourhealth111-pixel/Vibe-SkillsExplain trained machine learning models through feature attribution, local explanations, and behavior summaries. Use as an explicit/manual helper once a model already exists, not for training ownership, leakage auditing, or general ML strategy selection.ProductivityNo warnings★ 3.8K↓ —
- jetson-diagnosticNVIDIA/skillsRead-only Jetson health snapshot for identity, memory, GPU, thermal, power, storage, services, and top processes.ProductivityNo warnings★ 3.7K↓ —
- pufferlibforyourhealth111-pixel/Vibe-SkillsThis skill should be used when working with reinforcement learning tasks including high-performance RL training, custom environment development, vectorized parallel simulation, multi-agent systems, or integration with existing RL environments (Gymnasium, PettingZoo, Atari, Procgen, etc.). Use this skill for implementing PPO training, creating PufferEnv environments, optimizing RL performance, or developing policies with CNNs/LSTMs.ProductivityNo warnings★ 3.8K↓ —
jetson-memory-audit
NVIDIA/skills
ProductivityUpdated 14 hours ago
From the author
Measure Jetson DRAM/NvMap usage and verify before/after memory reclamation with live audit data.
Install
npx skills add NVIDIA/skills --skill jetson-memory-audit -a claude-code
Installs to .claude/skills/jetson-memory-audit/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Download .zip
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Runs bundled scriptsNo network use seenLicence: APACHE-2.0
Safety checks on SKILL.md
- Uses sudoLow
- Ships scripts we have not reviewedLow
Why 84
Security85
Provenance83
Maintenance100
Licence100
Adoption57
Files (8)
- BENCHMARK.md
- SKILL.md
- evals/evals.json
- references/DESIGN.md
- scripts/audit.sh
- scripts/drop_caches.sh
- skill-card.md
- skill.oms.sig