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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 1 minut
45.198 de skill-uri
- mongodb-natural-language-queryingmongodb/agent-skillsGenerate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.OficialDateFără avertismente★ 191↓ —Apare și în 3 alte depozite
- invalid-data-cleaningOpenSenseNova/SenseNova-Skills用于大规模Excel数据的预处理，通过统计总行数判断是否转换为Parquet格式以提升读写效率，并使用正则表达式清洗指定文本列（如仅保留中文字符），最后导出清洗后的文件并提供下载链接。DocumenteFără avertismente★ 5,9 K↓ —
- category-statisticsOpenSenseNova/SenseNova-Skills提取指定类别列并统计各类别数量与占比，生成高分辨率的柱状图、饼图等组合可视化报告，适用于分类数据的分布情况分析。AlteleFără avertismente★ 5,9 K↓ —
- regulatory-audit-generatorzebbern/claude-code-guideBuilds compliance checklists for business scenarios involving GDPR, PIPL, or advertising/data laws. Outputs a structured checklist with check items, legal basis, risk levels, and actionable recommendations. Triggered by requests like "run a compliance check," "GDPR/PIPL compliance," "pre-launch review," "privacy impact assessment (PIA/DPIA)," or asking if a feature is compliant.JuridicFără avertismente★ 4,7 K↓ —Apare și în 1 alt depozit
- humanize-chinesebrycewang-stanford/Auto-Empirical-Research-SkillsDetect and humanize AI-generated Chinese text. 20+ rule detection categories plus statistical features (sentence-length CV, short-sentence fraction, comma density, perplexity, GLTR, DivEye) plus scene-aware LR fusion (rule × 0.2 + LR × 0.8) trained on three scenes: general / academic / longform 长文本 (≥1500 字)。Unified CLI: ./humanize {detect,rewrite,academic,style,compare}. 8 style transforms (casual/zhihu/xiaohongshu/wechat/academic/literary/weibo/novel)。 Multi-paragraph rewriting (paragraph length CV、跨段 trigram 重复) plus best-of-N humanize (默认 N=10 取最低 LR)。165 replacement patterns + CiLin 同义词词林 38873 with collision blacklist。 Academic paper AIGC reduction for CNKI/VIP/Wanfang (知网/维普/万方 AIGC 检测降重)。 Pure Python, no dependencies, offline。v5.0.0 — HC3 fused 准确率 95%、学术 hero 100→35 (-65)、 工作汇报 96→13 (-83)、长篇博客 96→41 (-55)。 Use when user says: "去AI味", "降AIGC", "人性化文本", "humanize chinese", "AI检测", "AIGC降重", "去除AI痕迹", "文本改写", "论文降重", "知网检测", "维普检测", "AI写作检测", "让文字更自然", "detect AI text", "humanize text", "reduce AIGC scRedactareFără avertismente★ 4,8 K↓ —
- condition-filtering-and-large-file-optimizationOpenSenseNova/SenseNova-Skills根据数据规模动态选择处理策略。AlteleFără avertismente★ 5,9 K↓ —
- time-series-and-categorical-analysisOpenSenseNova/SenseNova-Skills对时间序列或分类数据进行多维度趋势分析、百分比清洗、绩效分级建模与预测，并生成高分辨率的可视化综合报告，适用于业务指标监控与预测场景。AlteleFără avertismente★ 5,9 K↓ —
- binlog-generationdotnet/skillsGenerate MSBuild binary logs (binlogs) for build diagnostics and analysis. USE FOR: adding /bl:{} to any dotnet build, test, pack, publish, or restore command to capture a full build execution trace, prerequisite for binlog-failure-analysis and build-perf-diagnostics skills, enabling post-build investigation of errors or performance. Requires MSBuild 17.8+ / .NET 8 SDK+ for {} placeholder; PowerShell must quote the complete switch as '-bl:{}'. DO NOT USE FOR: non-MSBuild build systems (npm, Maven, CMake), analyzing an existing binlog (use binlog-failure-analysis instead), binlog MCP startup failures (use troubleshoot-binlog-mcp).TestareFără avertismente★ 5,7 K↓ —
- pivot-table-cross-analysisOpenSenseNova/SenseNova-Skills利用交叉表与热力图对分类数据进行多维度占比分析，适用于奖项分布、绩效评估或市场占有率等结构化数据的清洗与可视化。AlteleFără avertismente★ 5,9 K↓ —
- build-parallelismdotnet/skillsAnalyze an MSBuild solution, solution filter, or Build.proj that schedules multiple project files. USE FOR: measured idle worker nodes, `-m` that does not scale, a serial ProjectReference critical path, graph builds, or an MSBuild task that builds a Projects list. Requires at least two distinct project files whose scheduling or throughput must be analyzed. DO NOT USE for non-MSBuild build systems.ProductivitateFără avertismente★ 5,7 K↓ —
- synthetic-monitoring-checksgrafana/skillsAuthor Grafana Cloud Synthetic Monitoring checks, with deep coverage of k6 scripted and browser checks: SM's single-VU/single-iteration execution model, assertions that actually fail probe_success (expect() and fail() vs bare check()), secrets, deterministic scripts, robust browser locators, local validation with k6 run, deployment via UI/API/Terraform, verifying probe_success, and rollback. Also helps choose the simplest sufficient check type (HTTP/ping/DNS/TCP, MultiHTTP, scripted, browser). Use when writing a synthetic check, monitoring a login/checkout/signup flow in production, converting a k6 script or an OpenAPI spec into a check, authoring a browser check, validating a user journey, or asking "is my site up from multiple regions". NOT for load, stress, or performance testing — SM runs one iteration per execution; for load tests use the grafana-k6 plugin or Grafana Cloud k6. For the broad Grafana Cloud Testing overview (SM + k6 Cloud + Faro), use the testing skill.OficialTestareFără avertismente★ 290↓ —
- range-reading-and-large-file-analysisOpenSenseNova/SenseNova-Skills读取多 Sheet Excel 文件，根据数据量动态选择处理策略，支持特定区域数据提取、大文件 Parquet 转换、统计分析及可视化图表生成。DocumenteFără avertismente★ 5,9 K↓ —
- word-analysisOpenSenseNova/SenseNova-SkillsWord (.docx/.doc) 文档全量解析。覆盖：正文/段落文本提取、表格数据提取、高亮/颜色格式读取、多文件汇总对比、嵌入图片转 caption。DocumenteFără avertismente★ 5,9 K↓ —
- property-patternsdotnet/skillsDiagnose and fix concrete MSBuild property defects in projects and existing shared-file hierarchies. USE FOR: conditions, defaults, append versus overwrite, last-write-wins values, OS/TFM checks, portable paths, normalization, and reviews centered on those property defects. Property defects in Directory.Build.* remain in scope, including overwritten values across parent/child imports and conditions that run before TargetFramework is set, even when the fix changes import order or moves a property group to .targets. DO NOT USE FOR: placement-only or import-only requests with no concrete property defect, such as discovering shared files or choosing which file owns a target or customization (use directory-build-organization); item operations; target structure; broad reviews without a concrete property defect; non-MSBuild work.RedactareFără avertismente★ 5,7 K↓ —
- excel-threshold-analysis-and-stylingOpenSenseNova/SenseNova-Skills根据 Excel 数据量级自动判断处理策略，执行数值列清洗、条件过滤，并使用 openpyxl 对符合条件的单元格进行样式标记与导出。DocumenteFără avertismente★ 5,9 K↓ —
- hunt-mfa-bypasselementalsouls/Claude-BugHunterHunt MFA / 2FA bypass — 7 distinct patterns. (1) MFA not enforced on sensitive endpoints (password change, email change accept without MFA challenge), (2) MFA-step skip via direct navigation to post-login URL, (3) MFA-token replay (same code accepted twice), (4) brute-force the 6-digit OTP without rate limit (10^6 attempts at server speed), (5) race condition on OTP validation, (6) recovery-code dump via /api/me, (7) backup factor downgrade (SMS factor with no rate limit). Plus the chain: cookie theft + password oracle + no step-up = ATO without MFA challenge. Detection: trace auth flow in Burp, find every state transition, check if MFA is middleware-gated vs per-endpoint, check OTP entropy and rate limit on OTP-validate. Validate: attacker session reaching post-MFA state. Use when hunting auth bypass, MFA flows, chaining primitives toward ATO.InginerieFără avertismente★ 5,3 K↓ —
- testability-obstacledotnet/skillsMUST USE for C#/.NET deterministic tests that require the smallest production seam for DateTime/Task.Delay/File/Environment/Guid/Random, static API preservation, nested/parallel overrides, or no real I/O. USE ONLY when the target workspace contains C# source plus a .csproj or .sln. DO NOT USE for audits, bulk migration, code that already has an injectable seam, or an explicit migration to a user-named existing abstraction (migrate-static-to-wrapper). Use instead of general test generation when the requested test is impossible without a production edit and seam selection is still open.TestareFără avertismente★ 5,7 K↓ —
- internet-courtinternet-court/internet-court-skillEntry point for Internet Court — the trust layer for agent-to-agent commerce. Use whenever an agent needs to transact with another agent or a paid service, or a user mentions agent payments, paid APIs (HTTP 402/x402), wallet custody or trust concerns, spending mandates, delegated permissions (ERC-7710/7715), escrow, agent identity or reputation (ERC-8004), negotiation between agents (A2A), agent jobs (ERC-8183), machine payments (MPP, AP2), supervision of agent behavior, revocation, verification, or dispute resolution (GenLayer) — even if they never say "Internet Court". Routes to the vendored protocol skills and connector skills in this package.AlteleFără avertismente★ 7 K↓ —
- sn-report-format-discoveryOpenSenseNova/SenseNova-Skills用于用户希望推荐研究成品形式，或最终形式无法从需求中直接判断时。把需求解析为一个简短的 format 字符串，不创建格式文件或 schema。AlteleFără avertismente★ 5,9 K↓ —
- heliusinternet-court/internet-court-skillBuild Solana applications with Helius infrastructure. Covers transaction sending (Sender), asset/NFT queries (DAS API), real-time streaming (WebSockets, Laserstream), event pipelines (webhooks), priority fees, wallet analysis, and agent onboarding.DevOpsFără avertismente★ 7 K↓ —Apare și în 1 alt depozit
- sn-da-large-file-analysisOpenSenseNova/SenseNova-Skills万行以上 Excel 数据集的高性能分析引擎。提供 openpyxl read_only 流式读取（iter_rows 支持 10 万行以上）、Parquet 转换加速、内存优化、分块处理和大文件写入模式。**遇到以下任一情况就主动使用本 skill**：①数据行数 ≥ 10k（由 sn-da-excel-workflow 的行数评估步骤触发）；②用户出现触发词：大文件 / 大数据量 / 性能优化 / 内存不足 / OOM / 百万行 / 十万行 / 流式读取 / Parquet / 分块处理 / large file / big data / streaming read / chunked processing；③直接使用 pd.read_excel() 导致超时或内存溢出；④用户明确要求对大规模数据集进行高性能处理。仅不用于：小于 10k 行的常规 Excel 分析（使用 sn-da-excel-workflow 即可）。DocumenteFără avertismente★ 5,9 K↓ —
- commit-koepoko77-ai/im-not-aiAI(Claude 등)가 제안한 한글 커밋 메시지의 사무적·번역투 어휘("~을 수행함", "~을 진행함", "~적 개선을 실시함" 등)를 실제 개발자가 쓰는 자연스러운 한국어 커밋 메시지로 다듬는 스킬. humanize-korean과 달리 산문 문단이 아니라 1~2줄짜리 커밋 메시지 register에 특화되어 진단·청킹 없이 단일 콜로 즉시 처리한다. 트리거 — "커밋 메시지 자연스럽게", "커밋 메시지 다듬어줘", "이 커밋 메시지 AI 티 나", "commit message 한국어로 자연스럽게", "커밋 메시지 어색해", "커밋 메시지 사람처럼".InginerieFără avertismente★ 6,3 K↓ —
- humanize-scanepoko77-ai/im-not-ai한글 글에 AI 티가 얼마나 있는지 재고, 실제로 고치면 어떻게 되는지 표본으로 보여주는 정찰 스킬. 실측 판별력 상위 6개만 본다. 워크스페이스·진단·게이트·서브에이전트 없이 이 대화 안에서 끝낸다(파일 0개, 서브에이전트 0회). 손볼 게 많다고 나오면 전수 윤문은 humanize-korean(=/humanize)으로 넘긴다. 트리거 — "이 글 AI 같아?", "AI 티 있나 봐줘", "스캔해줘", "윤문 돌릴 값어치 있나", "AI 티 점수", "quick humanize", "/humanize-scan".RedactareFără avertismente★ 6,3 K↓ —
- melonjs-physicsmelonjs/melonJSUse this skill for collision, physics bodies, movement, and spatial queries in melonJS — the built-in SAT world and the planck/matter adapters. Covers bodyDef vs Body, collision types and masks, the collision callback family and their firing rules, raycast/queryAABB/querySphere, the behaviour differences between adapters, and which one to pick for a given game. Triggers on: which physics engine, choosing an adapter, rotation collision, rotating body, torque, joints, stacking, Body, bodyDef, collision, collisionType, collisionMask, onCollision, onCollisionStart, onCollisionActive, raycast, queryAABB, querySphere, PlanckAdapter, MatterAdapter, gravity, velocity, applyForce, isGrounded, SAT.ȘtiințăFără avertismente★ 6,4 K↓ —
tao-finetune-video-clip
NVIDIA/skills
MediaActualizat acum 4 ore
De la autor
InternVideo2-CLIP L14 (TAO video_clip) for video-text retrieval, zero-shot classification, embedding extraction, LoRA fine-tuning, ONNX export, and TensorRT deployment. Use when the user asks to "fine-tune IV2CLIP", "run video_clip train/evaluate/inference/export", "build a Video-CLIP TensorRT engine", "InternVideo2-CLIP on KPI chunks", or "TAO video_clip on vadr1_chunks JSON".
Instalare
npx skills add NVIDIA/skills --skill tao-finetune-video-clip -a claude-code
Se instalează în .claude/skills/tao-finetune-video-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 (17)
- BENCHMARK.md
- SKILL.md
- config/skillspector-baseline.yaml
- eval.config
- evals/evals.json
- references/skill_info.yaml
- references/spec_template_deploy_evaluate.yaml
- references/spec_template_deploy_inference.yaml
- references/spec_template_evaluate.yaml
- references/spec_template_export.yaml
- references/spec_template_gen_trt_engine.yaml
- references/spec_template_inference.yaml
- încă 5