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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 2 minute
45.198 de skill-uri
- excel-data-analysis-and-report-generationOpenSenseNova/SenseNova-Skills从Excel提取多类型数据，并生成包含可视化图表与下载链接的综合分析报告。DateFără avertismente★ 5,9 K↓ —
- excel-conditional-comparison-and-large-file-processingOpenSenseNova/SenseNova-Skills对比Excel多表中的特定系数并对异常值进行颜色标记。DocumenteFără avertismente★ 5,9 K↓ —
- large-file-conditional-formattingOpenSenseNova/SenseNova-Skills根据Excel总行数自动切换Parquet加速读取，计算特定维度的时间序列平均值，并使用openpyxl输出带有条件格式（如低于均值标绿）和自定义样式的分析报告。DocumenteFără avertismente★ 5,9 K↓ —
- excel-smart-analysis-and-cleaningOpenSenseNova/SenseNova-Skills对多 Sheet Excel 进行智能清洗、跨表核对与可视化分析。。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↓ —
- 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↓ —
- grouped-statisticsOpenSenseNova/SenseNova-Skills对多 Sheet 的 Excel 文件进行行数统计、数据合并与前向填充。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↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- sn-da-non-spreadsheet-analysisOpenSenseNova/SenseNova-SkillsWord / PDF / PPT 文档解析与数据分析引擎。覆盖三类文件格式的全量提取、表格数值化、图表理解与跨文档汇总分析。**遇到以下任一情况就主动使用本 skill**：①用户上传或指定了 .docx / .doc / .pdf / .pptx / .ppt 文件并要求分析、提取或统计其中内容；②用户出现触发词：Word分析 / PDF解析 / PPT提取 / 文档分析 / 报告解析 / 幻灯片分析 / 发票提取 / 合同分析 / 文档统计 / 错别字 / 语病 / 字号检查 / 简历分析 / 多文档对比；③任务涉及从文档中提取表格、数值、图表、格式（颜色/高亮/字号）、组织架构、时间线等结构化信息。仅不用于：Excel/CSV 数据分析（使用 sn-da-excel-workflow）、纯图片分析（使用 sn-da-image-caption）。DateFără avertismente★ 5,9 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↓ —
- 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↓ —
- antislop-layoutmobilemiqdadbadjuber/anti-slopMobile layout skill for antislop. Use for layouts that reflow across screen sizes, phone to desktop: grids, overflow, tap targets. Load with the core.AlteleFără avertismente★ 7,2 K↓ —
- replica-buildJakeschincariol/replica-skillRebuilds an app screen by screen from the recon map: app shell first, then the core flow as a vertical slice, then every screen with all its states, ticking off the feature matrix as it goes. Writes every line fresh, never the original's code, assets or copy. Use when the user says "build the clone", "build screen S07", "start building", "rebuild this screen", "implement the booking page", or after /replica-design.DesignFără avertismente★ 5,6 K↓ —
- sn-updateOpenSenseNova/SenseNova-SkillsUpdate SenseNova Skills (the sn-* bundle) inside an OpenClaw or hermes-agent install. ALWAYS use this skill when the user says any of: "update SenseNova skills", "update SN skills", "更新 sensenova skills", "更新 sn skills", "刷新 sn-*", "升级 sn-* skills", or names a specific sn-* skill to update (e.g. "更新 sn-ppt-standard", "refresh sn-image-base"). Default scope is the whole sn-* bundle; if the user names specific skills, update ONLY those.MediaFără avertismente★ 5,9 K↓ —
- antislop-codemiqdadbadjuber/anti-slopCode comment hygiene for AI coding agents: remove generic AI-slop comments, keep the valuable ones, never touch the code.InginerieFără avertismente★ 7,2 K↓ —Apare și în 1 alt depozit
- self-awarenessaipoch/open-scienceInspect Open-Science's JavaScript control REPL, discover managed Project files, Sessions, and Agent Frames, and safely feature-gate host.* calls with host.capabilities(). Use when an Agent needs to discover available host APIs, locate an Artifact or Upload Version, diagnose a Session, or read a Frame transcript in the current Project.ȘtiințăFără avertismente★ 5,4 K↓ —
- proteinmpnnaipoch/open-scienceInverse-fold a protein backbone (PDB structure) into amino-acid sequence with ProteinMPNN (Dauparas et al. 2022, github.com/dauparas/ProteinMPNN). Reach for this skill to run sequence design on RFdiffusion backbones, to redesign one chain of a PDB while holding interface residues fixed, or to generate a temperature-swept set of sequences for downstream folding.DesignFără avertismente★ 5,4 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↓ —
- diffdockaipoch/open-sciencePredict small-molecule binding poses with DiffDock-L (Corso et al. 2023/2024, github.com/gcorso/DiffDock) — blind diffusion docking that places a ligand into a protein pocket without a predefined search box and ranks the samples with a learned confidence model. Reach for this skill to dock a SMILES or SDF against a PDB, to generate ranked 3D poses for a small fragment library, or to get a starting pose for downstream rescoring. DiffDock predicts geometry, not affinity.ȘtiințăFără avertismente★ 5,4 K↓ —
prisma-driver-adapter-implementation
prisma/skills
OficialDateActualizat acum 4 zile
De la autor
Required reference for Prisma ORM 7 SQL driver adapter work. Use when implementing or modifying adapters, adding database drivers, or touching SqlDriverAdapter, Transaction, savepoint, result mapping, or DriverAdapterError behavior. Covers current transaction lifecycle, optional savepoint hooks, original database-error preservation, and verification.
Instalare
npx skills add prisma/skills --skill prisma-driver-adapter-implementation -a claude-code
Se instalează în .claude/skills/prisma-driver-adapter-implementation/ · 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: MIT
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De ce 90
Securitate100
Proveniență100
Întreținere100
Licență100
Adopție33
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- SKILL.md