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.
45,424 skills from 2,188 repositories · updated 12 minutes ago
44,389 skills
- provider-oracleswiltodelta/remove-ai-watermarksRun hash-bound Google, OpenAI, Microsoft, or Meta watermark-oracle checks for this repository. Use for provider verification, multi-account Gemini checks, SynthID Detector checks at synthid.com, isolated Playwright checks, or recording oracle evidence. Walk the existing plan automatically when a task needs a provider verdict.TestingNo warnings★ 6.1K↓ —
- signal-discoverywiltodelta/remove-ai-watermarksDiscover missing AI provenance and watermark coverage in the remove-ai-watermarks library from fresh or historical corpora, then validate detection and removal parity. Use for corpus gap mining, periodic signal audits, new-provider discovery, or deciding whether old retained data must be replayed. Do not use for ordinary per-file identification or removal.OtherNo warnings★ 6.1K↓ —
- humanize-koreanepoko77-ai/im-not-aiAI(ChatGPT·Claude·Gemini)가 쓴 한글 텍스트를 사람이 쓴 글처럼 윤문한다. 번역투·영어 인용 과다·기계적 병렬·관용구·피동 남용·접속사 남발·리듬 균일·이모지/불릿 과다 등 10대 카테고리 70개 AI 티 패턴을 탐지·분류해 내용은 한 글자도 건드리지 않고 문체·리듬·표현만 자연스럽게 재작성한다. 트리거 — "AI 티 없애줘", "AI 윤문", "ChatGPT 티 제거", "번역투 고쳐", "사람이 쓴 것처럼", "humanize Korean". 단순 맞춤법 교정·번역·내용 추가는 대상 아님.WritingNo warnings★ 6.2K↓ —
- formatted-export-with-parquetOpenSenseNova/SenseNova-Skills从多Sheet Excel文件中识别指定条件的记录，并将筛选结果以整行标红格式导出为Excel文件，适用于数据清洗、条件筛选与可视化标记场景。DocumentsNo warnings★ 5.9K↓ —
- excel-multi-sheet-dynamic-analysisOpenSenseNova/SenseNova-Skills用于分析包含多个Sheet的Excel文件，动态判断数据量级以决定是否转换为Parquet进行大文件处理，并支持跨Sheet的特定字段统计、数据清洗、交叉分析与可视化，最终生成带下载链接的汇总报告。DocumentsNo warnings★ 5.9K↓ —
- excel-conditional-filtering-optimizationOpenSenseNova/SenseNova-Skills根据多维数值条件筛选 Excel 数据并导出结果，支持大规模数据的自动性能优化处理。DocumentsNo warnings★ 5.9K↓ —
- excel-outlier-detection-and-highlightingOpenSenseNova/SenseNova-Skills识别 Excel 中的超限数值与错误单元格并进行高亮标注。DocumentsNo warnings★ 5.9K↓ —
- trend-analysisOpenSenseNova/SenseNova-Skills基于多维度数据进行分级评估与趋势预测，通过设定差异化增长率计算预测值，并生成对比可视化图表，适用于绩效评估、目标设定等场景。OtherNo warnings★ 5.9K↓ —
- single-sheet-reading-and-analysisOpenSenseNova/SenseNova-Skills读取并解析单个Excel工作表数据，支持合并单元格处理、数据清洗、交叉分析及多维度可视化，适用于需要从单表中提取关键指标并进行趋势模拟与图表生成的场景。DocumentsNo warnings★ 5.9K↓ —
- multi-sheet-reading-and-analysisOpenSenseNova/SenseNova-Skills用于读取多工作表Excel文件，动态评估数据量以启用Parquet大文件优化，并执行正则清洗、分类汇总、线性拟合及生成带格式的图表与结果文件。DocumentsNo warnings★ 5.9K↓ —
- large-excel-analysis-and-formattingOpenSenseNova/SenseNova-Skills用于处理多Sheet大型Excel文件，支持大文件Parquet格式转换提速，并使用openpyxl生成带条件高亮和自定义样式的格式化Excel报告及下载链接。DocumentsNo warnings★ 5.9K↓ —
- dynamic-large-file-parquet-analysisOpenSenseNova/SenseNova-Skills动态统计Excel总行数，当数据量过大（≥10000行）时自动转换为Parquet格式加速读取，并对指定目标列进行条件筛选、分类汇总与结果导出，适用于超大体积Excel文件的快速读取与统计分析。DocumentsNo warnings★ 5.9K↓ —
- excel-sheet-filter-exportOpenSenseNova/SenseNova-Skills动态统计多Sheet Excel文件行数以判断大文件处理逻辑，并根据特定条件筛选数据、重命名字段后导出为包含下载链接的新Excel文件，适用于多Sheet数据探查与条件过滤导出场景。DocumentsNo warnings★ 5.9K↓ —
- git-commitThinkInAIXYZ/deepchatGenerate well-formatted git commit messages following conventional commit standardsEngineeringNo warnings★ 6.4K↓ —
- memcodeThinkInAIXYZ/deepchatUse the enabled Memcode MCP connection to explicitly save approved facts and recall relevant memories across DeepChat conversations. Never save a transcript or retrieve memory automatically.ProductivityNo warnings★ 6.4K↓ —
- deepchat-cliThinkInAIXYZ/deepchatUse DeepChat's bundled CLI control plane for model inference, image/video/speech generation, transcription, OCR, artifact inspection, public configuration, Skills, and MCP operations. Activate when a user asks to invoke DeepChat capabilities that are not already exposed as a more specific tool, compare models, run a benchmark, inspect DeepChat runtime state, or manage DeepChat through the CLI.EngineeringNo warnings★ 6.4K↓ —
- code-reviewThinkInAIXYZ/deepchatComprehensive code review assistant that analyzes code quality, security, and best practicesEngineeringNo warnings★ 6.4K↓ —
- add-providerThinkInAIXYZ/deepchatAdd a DeepChat LLM provider through explicit reviewed source changes. Use when a developer asks Codex to add a provider, provider profile, upstream provider config, model catalog mapping, provider auth behavior, or a special provider adapter in this repository.PlanningNo warnings★ 6.4K↓ —
- agentic-workflowsdotnet/skillsRoute gh-aw workflow design/create/debug/upgrade requests to the right prompts.DesignNo warnings★ 5.7K↓ —
- thinktw93/WazaTurns rough ideas into approved, decision-complete plans before coding. Use when planning architecture, judging whether to build, or writing a handoff. Not for bug fixes or small edits.WritingNo warnings★ 7.4K↓ —Also in 1 other repo
- learntw93/WazaRuns a six-phase research workflow from source bundle to publish-ready output. Use when researching an unfamiliar domain or compiling materials into one reference. Not for quick lookups or single-file reads.ScienceNo warnings★ 7.4K↓ —Also in 1 other repo
- algorithmic-artanthropics/skillsCreating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.OfficialEngineeringNo warnings★ 183.4K↓ —Also in 9 other repos
- mongodb-mcp-setupmongodb/agent-skillsGuide users through configuring key MongoDB MCP server options. Use this skill when a user has the MongoDB MCP server installed but hasn't configured the required environment variables, or when they ask about connecting to MongoDB/Atlas and don't have the credentials set up.OfficialOtherNo warnings★ 190↓ —Also in 2 other repos
- designlang-tokensManavarya09/design-extractUse when styling UI for ramp.com — references the extracted design system tokens instead of inventing colors, spacing, or typography.DesignNo warnings★ 4.4K↓ —
mongodb-natural-language-querying
mongodb/agent-skills
OfficialDataUpdated 2 days ago
From the author
Generate 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.
Install
npx skills add mongodb/agent-skills --skill mongodb-natural-language-querying -a claude-code
Installs to .claude/skills/mongodb-natural-language-querying/ · 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
Instructions onlyNo network use seenLicence: APACHE-2.0
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