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.
45.604 skill-uri din 2.205 depozite · actualizat acum 17 ore
45.604 skill-uri
- dowhybrycewang-stanford/Auto-Empirical-Research-SkillsCausal inference framework for answering "does X cause Y?" beyond correlation. DoWhy (Microsoft Research) provides the identify-estimate-refute loop: define a causal graph (DAG), identify the causal effect using backdoor/frontdoor/instrumental variable criteria, estimate treatment effects with multiple estimators, and validate results with automated refutation tests. Use when: distinguishing causation from correlation, estimating treatment effects (ATE, ATT, CATE), designing and analyzing A/B tests with confounders, using instrumental variables, performing counterfactual reasoning ("what would have happened if..."), validating causal claims with sensitivity analysis, working with observational data where randomization is impossible, or any analysis where the question is "what is the CAUSAL effect of X on Y" rather than just "how do X and Y relate?"TestareFără avertismente★ 4,8 K↓ —
- fair-esm2aipoch/open-scienceEmbed proteins with Meta AI's ESM-2 (`fair-esm` package). Use this skill when: (1) Extracting per-residue or per-sequence embeddings for downstream ML, (2) Masked-LM likelihood / mutation effect scoring, (3) Contact prediction from a sequence.AlteleFără avertismente★ 5,4 K↓ —
- esmfold2aipoch/open-scienceBiohub ESMFold2 / ESMFold2-Fast all-atom co-folding (Candido et al. 2026, github.com/Biohub/esm). Single-sequence and MSA modes; protein, DNA, RNA, ligand (CCD/SMILES), modified residues. FoldBench Ab-Ag 50-55%, PPI 70-77% DockQ-pass. Also covers the ESMC-{300M,600M,6B} protein language models from the same release: masked-LM logits, hidden states, mutation scoring, contact prediction, and the SAE interpretability head. MIT-licensed weights on HuggingFace org `biohub`. Use this skill when: (1) Predicting complex structures with single-sequence input, (2) Validating designed binders with ESMFold2-Fast, (3) Running ESMFold2 with MSA input, (4) Getting ESMC embeddings or per-residue mutation scores, (5) Choosing kernel backend and sampling-step settings for paper-faithful throughput.ȘtiințăFără avertismente★ 5,4 K↓ —
- customizeaipoch/open-scienceUse when the user wants to create or manage a Specialist agent or create, revise, publish, or delete a Skill through the conversational `/Customize` entry. Routes Skill work to the internal skill-creator and handles Specialist work through the JavaScript host.agents SDK.PlanificareFără avertismente★ 5,4 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↓ —
- 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.AlteleFără avertismente★ 6,1 K↓ —
- 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↓ —
- vitestantfu/skillsVitest fast unit testing framework powered by Vite with Jest-compatible API. Use when writing tests, mocking, configuring coverage, or working with test filtering and fixtures.TestareFără avertismente★ 6 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↓ —
- computer-useThinkInAIXYZ/deepchatDrive native desktop apps through DeepChat's built-in Computer Use tools. Use when the user asks to operate, inspect, automate, or perform a GUI task in a real desktop application.ProductivitateFără avertismente★ 6,4 K↓ —
- unocssantfu/skillsUnoCSS instant atomic CSS engine, superset of Tailwind CSS. Use when configuring UnoCSS, writing utility rules, shortcuts, or working with presets like Wind, Icons, Attributify.DesignFără avertismente★ 6 K↓ —
- 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.InginerieFără avertismente★ 6,4 K↓ —
- 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.ProductivitateFără avertismente★ 6,4 K↓ —
- 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↓ —
- content-briefRyze-AI-Adgent/open-seo-mcp-skillsSERP-driven content brief for a target keyword — what ranks, what to cover, headings, questions, internal links from your own data. Use when asked for a "content brief", "outline to rank for X", "what should this article cover", or before writing any SEO page.MarketingFără avertismente★ 7,1 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↓ —
- top-web-vulnerabilitieszebbern/claude-code-guideThis skill should be used when the user asks to "identify web application vulnerabilities", "explain common security flaws", "understand vulnerability categories", "learn about injection attacks", "review access control weaknesses", "analyze API security issues", "assess security misconfigurations", "understand client-side vulnerabilities", "examine mobile and IoT security flaws", or "reference the OWASP-aligned vulnerability taxonomy". Use this skill to provide comprehensive vulnerability definitions, root causes, impacts, and mitigation strategies across all major web security categories.SecuritateFără avertismente★ 4,7 K↓ —
- ppt-analysisOpenSenseNova/SenseNova-SkillsPPT (.pptx/.ppt) 全量解析。覆盖:所有 slide 文本/表格/图表提取、嵌入图片 caption、纯图片 slide 渲染识别、数据标签提取。DocumenteFără avertismente★ 5,9 K↓ —
- multi-file-excel-parquet-analysisOpenSenseNova/SenseNova-Skills读取多 Sheet Excel 文件并统计规模,支持大文件向 Parquet 格式转换、分类数据统计及可视化报告生成。DocumenteFără avertismente★ 5,9 K↓ —
- feishu-toolsThinkInAIXYZ/deepchatUse the Feishu/Lark plugin MCP tools for Feishu documents, spreadsheets, knowledge content, and other matching workspace operations.AlteleFără avertismente★ 6,4 K↓ —
- mirrord-upmetalbear-co/mirrordHelps users run multiple concurrent mirrord sessions from a single mirrord-up.yaml (compose-style multi-service local debugging). Use when the user mentions mirrord up, mirrord-up.yaml, mirrord up init, debugging several related microservices together, or managing multiple mirrord sessions' lifecycle in one command.InginerieFără avertismente★ 5,4 K↓ —
- designlang-tokensManavarya09/design-extractUse when styling UI for sentry.io — references the extracted design system tokens instead of inventing colors, spacing, or typography.DesignFără avertismente★ 4,4 K↓ —
- 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↓ —
- 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↓ —
code-documenter
zebbern/claude-code-guide
De la autor
Use when adding docstrings, creating API documentation, or building documentation sites. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, tutorials, user guides.
Instalare
npx skills add zebbern/claude-code-guide --skill code-documenter -a claude-code
Se instalează în .claude/skills/code-documenter/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 91
Fișiere (9)
- SKILL.md
- references/api-docs-fastapi-django.md
- references/api-docs-nestjs-express.md
- references/coverage-reports.md
- references/documentation-systems.md
- references/interactive-api-docs.md
- references/python-docstrings.md
- references/typescript-jsdoc.md
- references/user-guides-tutorials.md