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.
45.198 de skill-uri din 2.196 de depozite · actualizat acum 18 minute
45.198 de skill-uri
- godot-ui-controlgamedev-skills/awesome-gamedev-agent-skillsBuild Godot 4.7 user interfaces with Control nodes: anchors and offsets for responsive layout, Container nodes (VBox/HBox/Grid/Margin) for automatic arrangement, Theme resources for consistent styling, and keyboard/gamepad focus navigation. Use when laying out a HUD, menu, or UI in a Godot project, working with Control/Container nodes, anchors, themes, or focus in a .tscn.DesignFără avertismente★ 4,6 K↓ —
- nansen-holder-analysisinternet-court/internet-court-skillIs this token held by quality wallets or retail noise? SM holder ratio, flow breakdown by label, and recent buyer quality.AlteleFără avertismente★ 7 K↓ —
- hunt-nosqlielementalsouls/Claude-BugHunterHunt NoSQL Injection — MongoDB operator injection ($where, $regex, $gt, $ne), CouchDB, Redis command injection, auth bypass via NoSQLi, data dump. Use when target uses MongoDB/Mongoose, CouchDB, Redis, or shows NoSQL error messages.AlteleFără avertismente★ 5,3 K↓ —
- hunt-nodejselementalsouls/Claude-BugHunterHunt Node.js specific vulnerabilities — Prototype Pollution → RCE chains (lodash/merge/assign), Express trust proxy misconfiguration, child_process/eval injection, template engine SSTI (EJS/Pug/Handlebars), path traversal in file servers, require() injection, environment variable exfil via /proc/self/environ. Use when target runs Node.js/Express/Fastify/NestJS/Koa.SecuritateFără avertismente★ 5,3 K↓ —
- line-chart-visualizationOpenSenseNova/SenseNova-Skills提取结构化数据并进行特征清洗与聚类分析，生成包含趋势对比、分布特征与参数敏感性的多维度综合可视化图表，适用于各类趋势预测与多维对比场景。AlteleFără avertismente★ 5,9 K↓ —
- prometheus-label-strategygrafana/skillsExpert evaluator for Prometheus label strategy on Grafana Cloud. Audits, designs, and improves label schemas using cardinality scoring, access-pattern alignment, static vs. dynamic label rules, histogram bucket discipline, and instrumentation hygiene. Prevents high cardinality at the source — in application code and scrape target labels — without dropping labels that make series unique (which breaks the data). For reducing the cost of series already in Grafana Cloud, routes to the adaptive-metrics skill. Use when the user asks to evaluate, audit, design, or improve Prometheus labels — or asks how to prevent high cardinality at the source. For "why is my Prometheus slow / expensive right now" triage, see prometheus-cardinality-troubleshooter.OficialDesignFără avertismente★ 290↓ —
- sn-ppt-storyOpenSenseNova/SenseNova-Skills当前 PPT 任务已由 sn-ppt-entry 建好 DECK_DIR（task_pack.json 与 info_pack.json 已写入）后，必须由本 skill 将 query、全部用户材料与已完成 Research 编排为唯一可编辑的 outline.md 时使用。本 skill 是 entry → 出口（standard / dazzle / creative）之间的强制中间环节：不允许执行 Agent 跳过本 skill 直接依据 task_pack / info_pack 即兴编写大纲，不允许出口 skill 代写或改写大纲；前置产物缺失时停止并返回 sn-ppt-entry 补齐，不得自行补做研究。ȘtiințăFără avertismente★ 5,9 K↓ —
- pie-chart-data-analysisOpenSenseNova/SenseNova-Skills对多Sheet Excel或CSV数据进行分类汇总统计，自动识别关键字段并生成包含占比、数值及美化饼图的可下载分析报告。DateFără avertismente★ 5,9 K↓ —
- statistical-distribution-and-outlier-analysisOpenSenseNova/SenseNova-Skills执行数值型数据的分布分析与异常值检测，支持通过正则表达式从文本中提取误差项并生成高分辨率的箱线图与直方图报告。AlteleFără avertismente★ 5,9 K↓ —
- database-observabilitygrafana/skillsSet up Grafana Cloud Database Observability for MySQL and PostgreSQL — enables `pg_stat_statements` / Performance Schema, creates a least-privilege monitoring user, configures the `database_observability.postgres` / `database_observability.mysql` Alloy components, ships query samples + visual explain plans + RED metrics + schema details to Grafana Cloud, and correlates slow queries with application traces via `db.statement` / `db.system` OTel attributes. Use when monitoring database performance, diagnosing slow queries, setting up DB observability for RDS / Aurora / Cloud SQL / Azure Database / self-managed instances, correlating DB metrics with APM, or alerting on query latency — even when the user says "my database is slow", "find the slow queries", or "monitor RDS" without saying "observability".OficialDevOpsFără avertismente★ 290↓ —
- numeric-format-normalizationOpenSenseNova/SenseNova-Skills对 Excel 数据进行数值格式标准化与清洗，支持大规模数据的 Parquet 转换流程，并完成关键指标的合计核对与结果文件导出。DocumenteFără avertismente★ 5,9 K↓ —
- roblox-charactersgamedev-skills/awesome-gamedev-agent-skillsBuild respawn-safe Roblox character systems around Players, CharacterAdded/CharacterRemoving, Humanoid, HumanoidRootPart, Animator, R6/R15 rigs, movement, animations and markers, death, tools, accessories, ownership, and custom characters. Use when character scripts break after respawn, cache stale Humanoids, control movement or velocity, load AnimationTracks, handle death, equip Tools, modify avatars, or support custom player rigs.AlteleFără avertismente★ 4,6 K↓ —
- veida-imageNoudavepoon/buildwithclaudeGenerate an image from a text prompt with no API key, no account and no cost, using the free anonymous tier of Veida (veida.ai). Use when the user asks for a picture, an illustration, a blog cover, a mockup or an avatar and no image provider is configured. Two HTTP calls; returns a hosted image URL.MediaFără avertismente★ 3,7 K↓ —
- audit-augmentationtrailofbits/skillsAugments Trailmark code graphs with external audit findings from SARIF static analysis results, weAudit annotation files, and version-gated Trailmark 0.4.x binary-analysis graph exports. Maps findings to graph nodes by file and line overlap, creates severity-based subgraphs, and enables cross-referencing findings with pre-analysis data (blast radius, taint, etc.). Use when projecting SARIF results onto a code graph, overlaying weAudit annotations, importing binary graph findings, cross-referencing Semgrep, CodeQL, or binary-analysis findings with call graph data, or visualizing audit findings in the context of code structure.InginerieFără avertismente★ 7,8 K↓ —
- audio-mixZJU-REAL/Easel音频混合 / 混音：把旁白口播 + 背景音乐 + 音效混成一轨，BGM 自动循环补足并可闪避（旁白说话时自动压低 BGM 保证人声清晰）。当用户说 混音、音频混合、旁白加背景音乐、配音加BGM、人声和音乐混一起、加音效、音频叠加、BGM 压低、闪避、ducking、把配音和bgm合起来 时使用。基于 shared/scripts/audio_mix.py。与 audio-editing concat 区别：concat 是前后顺序拼接，本 SKILL 是同时叠加混音；与 video-editing bgm 区别：那个给视频配乐，本 SKILL 输出纯音频。MediaFără avertismente★ 4,1 K↓ —
- gsd:inboxdavepoon/buildwithclaudeTriage and review all open GitHub issues and PRs against project templates and contribution guidelinesInginerieFără avertismente★ 3,7 K↓ —
- video-intro-outroZJU-REAL/Easel视频片头 / 片尾：生成带标题、副标题、logo、关注引导的片头卡片和片尾卡片，并拼接到主视频（硬切或淡入淡出转场）。当用户说 片头、片尾、加片头片尾、开场卡片、结尾卡片、标题卡、关注引导页、订阅引导、视频开头加标题、结尾加点赞关注、intro、outro、片头动画 时使用。基于 shared/scripts/intro_outro.py 确定性 ffmpeg 封装。与 poster-hero 区别：poster-hero 出静态封面图，本 SKILL 出可拼接的视频卡片片段。MediaFără avertismente★ 4,1 K↓ —
- doca-capsNVIDIA/skillsUse this skill when the user wants to invoke the read-only doca_caps CLI to ask what DOCA sees on this host — listing DOCA devices and PCIe addresses, listing representor devices, asking which DOCA libraries are available on the current OS, checking per-device per-library capabilities, scoping output to a specific PCIe address, or capturing a side-effect-free capability snapshot for debug or install smoke-test. Trigger even when the user does not explicitly mention "doca_caps" or "capabilities print tool" — typical implicit phrasings include "what does DOCA actually see on this box", "is my BlueField PF visible to DOCA", "is Flow available on my RHEL host", "enumerate VF representors for pf0", "doca_caps: command not found", or "empty output for RDMA, is the tool broken". Refuse and route elsewhere for DOCA installation (doca-setup owns it; never walk the steps), library-internal capability matrices (Flow pipe creation, RDMA verbs features), streaming telemetry / DTS, or modifying the shipped binary.TestareFără avertismente★ 3,7 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★ 3,7 K↓ —
- verifyzenbu-labs/terminal-browserDrive an engine app headlessly in a pty, record a video of the whole verification, and open a summary page (video + timeline + checks) with pixel open.MediaFără avertismente★ 4,3 K↓ —
- doca-pccNVIDIA/skillsUse this skill when the user is doing hands-on host-side DOCA PCC work to load a CUSTOM Programmable Congestion Control algorithm onto a BlueField DPU — creating per-port `doca_pcc` contexts, loading a `dpacc`-compiled `doca_pcc_app` onto the `doca_dev` for the RoCE-bearing port, parameterizing it, walking triple-axis capability discovery (DOCA cap-query + DPA-capable BlueField + firmware custom-PCC slot enabled), or debugging `DOCA_ERROR_*` from `doca_pcc_*`. Trigger even without explicit "DOCA PCC" phrasing — implicit forms include "loading my own congestion control onto a BF port", "DOCA_ERROR_NOT_PERMITTED on algorithm load", "DOCA_ERROR_DRIVER when I attach my custom algorithm", "my custom rate-update isn't affecting RoCE traffic", or "load succeeds but no on-wire change". Refuse and route elsewhere for DPA-side algorithm-body design, the `pcc_counters` CLI, default factory PCC in ConnectX firmware, or setting up the RDMA / RoCE traffic — those belong to other skills.DesignFără avertismente★ 3,7 K↓ —
- skill-audience-profilerZJU-REAL/Easel构建目标受众画像：分析粉丝人群特征、痛点需求、内容偏好和触达渠道，输出可执行的受众画像卡。 当用户说"受众画像""粉丝画像""我的用户是谁""目标人群""用户痛点""受众分析""谁在看我"时使用。 构建的是受众/粉丝画像，创作者自己的声音画像用 skill-voice-builder。AlteleFără avertismente★ 4,1 K↓ —
- skill-seo-qualityZJU-REAL/Easel平台原生搜索流量优化：把内容做成能被平台搜索到的样子。 校验并优化标题/正文关键词布局、话题标签搜索权重、封面/首帧文字关键词、 搜索流量 vs 推荐流量的取舍。覆盖小红书、抖音、知乎、公众号、B站、微博。 当用户说"SEO 检查"、"搜索优化"、"关键词布局"、"搜不到我的内容"、 "怎么被搜到"、"话题标签怎么选"、"搜一搜优化"、"发布前校验"时使用。 网页/博客的 Meta/OG/Slug/E-E-A-T 校验作为可选模式保留（见 references）。MarketingFără avertismente★ 4,1 K↓ —
- doca-staNVIDIA/skillsUse this skill when the user builds an NVMe-over-Fabrics storage target on BlueField with DOCA STA — instantiating doca_sta, declaring doca_sta_subsystem NQNs and namespaces over local NVMe disks via doca_sta_be, validating platform support with doca_sta_cap_is_supported, sizing I/O queue depth, or decoding DOCA_ERROR_* statuses such as IO_FAILED on NVMe reads. Also load it for implied asks like "Identify Controller times out over RoCE", "offload the nvmf target", "NVMe-oF Connect never completes", or "16 I/O queues at depth 1024 — supported?". Refuse and route to the proper owner for raw RDMA movement, packet I/O, steering rules, initiator-side NVMe, or SDK install.AlteleFără avertismente★ 3,7 K↓ —
doca-bench
NVIDIA/skills
FinanțeActualizat acum 6 ore
De la autor
Run `doca_bench` (DOCA 2.7.0 or newer) to measure throughput, bulk latency, precision latency, or maximum bandwidth for RDMA, Compress, AES-GCM, SHA, DMA, EC, Ethernet, Comch, or GPUNetIO on a host or BlueField Arm. Use it to discover enabled benchmark libraries, capture a reproducible command/version/device/environment baseline, compare stable runs against a declared tolerance, or diagnose configuration, device-binding, workload-precondition, and measurement failures. Trigger for requests such as measuring BlueField compression speed, NIC RDMA throughput, crypto latency, or a pre-upgrade baseline. Do not use for application end-to-end timing, custom benchmark code, DOCA installation, or binary patches.
Instalare
npx skills add NVIDIA/skills --skill doca-bench -a claude-code
Se instalează în .claude/skills/doca-bench/ · 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 (8)
- BENCHMARK.md
- CAPABILITIES.md
- SKILL.md
- SKILLCARD.yaml
- TASKS.md
- evals/evals.json
- skill-card.md
- skill.oms.sig