所有 Skills
找到 8171 个 Skills
Skills 列表

acquire-codebase-knowledge
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
github
gtm-ai-gtm
Go-to-market strategy for AI products. Use when positioning AI products, handling "who is responsible when it breaks" objections, pricing variable-cost AI, choosing between copilot/agent/teammate framing, or selling autonomous tools into enterprises.
github
gtm-board-and-investor-communication
Board meeting preparation, investor updates, and executive communication. Use when preparing board decks, writing investor updates, handling bad news with the board, structuring QBRs, or building board-level metric discipline. Includes the "Three Things" narrative model, the 4-tier metric hierarchy, and the pre-brief pattern that prevents board surprises.
github
gtm-enterprise-account-planning
Strategic account planning and execution for enterprise deals. Use when planning complex sales cycles, managing multiple stakeholders, applying MEDDICC qualification, tracking deal health, or building mutual action plans. Includes the "stale MAP equals dead deal" pattern.
github
gtm-partnership-architecture
Build and scale partner ecosystems that drive revenue and platform adoption. Use when building partner programs from scratch, tiering partnerships, managing co-marketing, making build-vs-partner decisions, or structuring crawl-walk-run partner deployment.
github
semantic-kernel
Create, update, refactor, explain, or review Semantic Kernel solutions using shared guidance plus language-specific references for .NET and Python.
github
gtm-0-to-1-launch
Launch new products from idea to first customers. Use when launching products, finding early adopters, building launch week playbooks, diagnosing why adoption stalls, or learning that press coverage does not equal growth. Includes the three-layer diagnosis, the 2-week experiment cycle, and the launch that got 50K impressions and 12 signups.
github
aws-cdk-python-setup
Setup and initialization guide for developing AWS CDK (Cloud Development Kit) applications in Python. This skill enables users to configure environment prerequisites, create new CDK projects, manage dependencies, and deploy to AWS.
github
gtm-technical-product-pricing
Pricing strategy for technical products. Use when choosing usage-based vs seat-based, designing freemium thresholds, structuring enterprise pricing conversations, deciding when to raise prices, or using price as a positioning signal.
github
sandbox-npm-install
Install npm packages in a Docker sandbox environment. Use this skill whenever you need to install, reinstall, or update node_modules inside a container where the workspace is mounted via virtiofs. Native binaries (esbuild, lightningcss, rollup) crash on virtiofs, so packages must be installed on the local ext4 filesystem and symlinked back.
github
dotnet-reverse
.NET / C# 二进制逆向。当目标是 .NET assembly(PE 头含 CLR、.exe/.dll 托管程序)、C# 编译产物(含 NativeAOT)、红队 Sharp* 工具(Rubeus / SharpHound / SharpHound 等)、.NET 混淆程序(ConfuserEx / SmartAssembly / Babel / Eazfuscator)、.NET loader / info-stealer / 套壳 malware 时使用。优先用 dnSpyEx + de4dot,需要 AI 直接操作时联动 dnSpy MCP。不用于纯 native 二进制(走 reverse-engineering / ida-reverse)。
zhaoxuya520
js-reverse
在使用 js-reverse-mcp 做前端 JavaScript 逆向时使用,适用于签名链路定位、页面观察取证、运行时采样、本地补环境复现与证据化输出。优先适配当前环境里的 js-reverse_* 工具,需要更强的浏览器/CDP/Hook 面时联动 jshookmcp。
zhaoxuya520
scaffolding-oracle-to-postgres-migration-test-project
Scaffolds an xUnit integration test project targeting Oracle in .NET solutions. Creates the test project, transaction-rollback base class, and seed data manager. Use only during Phase 3, before writing Oracle baseline integration tests. Do not invoke during Phase 6 — the PostgreSQL test project is produced by migrating this project, not by running this skill again.
github
gtm-product-led-growth
Build self-serve acquisition and expansion motions. Use when deciding PLG vs sales-led, optimizing activation, driving freemium conversion, building growth equations, or recognizing when product complexity demands human touch. Includes the parallel test where sales-led won 10x on revenue.
github
oo-component-documentation
Create or update standardized object-oriented component documentation using a shared template plus mode-specific guidance for new and existing docs.
github
academic-paper
由 12 个 Agent 协作组成的学术论文写作流水线。提供 11 种工作模式(全流程/规划/大纲/修改/审稿意见辅导/摘要/文献综述/格式转换/引用检查/AI使用声明/审稿反驳审计)。支持 6 种论文类型、5 种引用格式、中英双语摘要,可导出 LaTeX、DOCX(基于 Pandoc)、PDF 及 Markdown。内置文风校准(Style Calibration)、写作质量检查(Writing Quality Check)以及带“铁律(IRON RULE)”标记的违规避坑指南。触发词包含:write paper, academic paper, guide my paper, parse reviews, audit my rebuttal, check my response draft, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見, 評估回覆, 논문 작성, 초록 작성, 논문 수정, 논문 계획을 도와줘, 심사 의견 반영, 답변서 점검, AI 사용 고지。
imbad0202
academic-paper-reviewer
基于动态审稿人人设的多视角学术论文审稿工具。模拟 5 位具备特定领域专业知识的独立审稿人(主编 + 3 位同行审稿人 + 魔鬼代言人)。支持全盘审稿、修回复审(验证模式)、快速评估、聚焦研究方法、苏格拉底式引导以及审稿人校准模式。触发词包括:review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy, 논문 심사, 동료 심사, 모의 심사, 심사자 관점에서 평가, 심사자 보정。
imbad0202
scikit-learn
使用 scikit-learn 在 Python 中进行机器学习。适用于监督学习(分类、回归)、无监督学习(聚类、降维)、模型评估、超参数调优、预处理或构建机器学习流水线。提供算法、预处理技术、流水线和最佳实践的全面参考文档。
k-dense-ai
当用户想要对PDF文件进行任何操作时,使用此技能。这包括从PDF中读取或提取文本/表格,将多个PDF合并为一个,拆分PDF,旋转页面,添加水印,创建新PDF,填写PDF表单,加密/解密PDF,提取图像,以及对扫描的PDF进行OCR使其可搜索。如果用户提到.pdf文件或要求生成PDF文件,请使用此技能。
k-dense-ai
exploratory-data-analysis
对明确支持的科学文件执行有界、本地的探索性分析。用于脱敏的CSV/TSV/JSON配置文件;可选的NumPy、HDF5、FASTA/FASTQ和基本图像元数据检查;缺失性/泄漏审计;异常值和变换敏感性;以及严格的EDA报告框架。其他领域格式仅作参考,未知格式默认拒绝。
k-dense-ai
markitdown
使用 Microsoft MarkItDown 将异构文档和选定的 URI 转换为 Markdown,用于文本分析、搜索和 LLM/RAG 摄取。涵盖安全的本地转换、流、Office/PDF/数据格式、批处理工作流、插件、视觉 OCR、Azure 提取以及官方 MCP 服务器。
k-dense-ai
markdown-mermaid-writing
全面的 Markdown 和 Mermaid 图表编写技能。在创建任何科学文档、报告、分析或可视化时使用。将基于文本的图表确立为默认文档标准,包含完整的样式指南(markdown + mermaid)、24 种图表类型参考和 9 种文档模板。
k-dense-ai
statsmodels
用于Python的统计模型库。当您需要具有详细诊断、残差和推断的特定模型类(OLS、GLM、混合模型、ARIMA)时使用。最适合计量经济学、时间序列、带有系数表的严格推断。如需带APA报告的引导式统计检验选择,请使用statistical-analysis。
k-dense-ai
seaborn
与 pandas 集成的统计可视化。用于快速探索分布、关系和分类比较,具有吸引人的默认设置。最适合箱线图、小提琴图、成对图和热力图。基于 matplotlib 构建。对于交互式绘图使用 plotly;对于出版样式使用 scientific-visualization。
k-dense-ai