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Found 8,786 Skills
Implements Syncfusion .NET MAUI SfPdfViewer for cross-platform PDF viewing, navigation, annotations, form filling/validation, text search/selection, e-signatures, redaction, printing, and toolbar/UI customization. Use when working with PDF viewer setup, document annotations, form fields, or signature workflows in MAUI apps.
Clinical Decision Support System (CDSS) development patterns. Drug interaction checking, dose validation, clinical scoring (NEWS2, qSOFA), alert severity classification, and integration into EMR workflows.
Generates ZK Framework ZUL pages (.zul) through a structured 4-step workflow: requirements clarification, ZUL generation, validation, and controller generation. Supports both MVC (Composer-based) and MVVM (ViewModel-based) patterns, ZK 9/10, and visual analysis for screenshot-to-ZUL conversion. Use when the user asks to create a ZUL page, build ZK UI components (forms, grids, dashboards, borderlayouts), or convert an image/mockup to ZUL code.
Guides the agent through installing, authenticating, configuring, and using the Capawesome CLI (@capawesome/cli). Covers installation, interactive and token-based authentication, project linking via capawesome.config.json, the full command reference (app management, native builds, live updates, certificates, environments, channels, deployments, destinations, devices), CI/CD integration with token auth and JSON output, and diagnostics via the doctor command. Do not use for Capawesome Cloud feature setup (native builds workflow, live updates workflow, app store publishing) — use the capawesome-cloud skill instead.
Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.
Set up and configure Google's release-please for automated versioning, changelog generation, and publishing via GitHub Actions. Covers pipeline creation, Conventional Commits formatting, pre-release workflows, monorepo configuration, and troubleshooting release pipelines. Use this skill whenever the user wants to automate releases, set up CI/CD for publishing, configure version bumping, write release-please-compatible commit messages, tag versions automatically, publish to npm/PyPI/crates.io/Maven/Docker, or troubleshoot why a release PR wasn't created. Activate even if the user doesn't mention "release-please" by name — phrases like "automate my npm releases", "set up GitHub Actions for publishing", "how do I tag versions automatically", "changelog generation", "semver automation", or "pre-release workflow" all indicate this skill. For commit message guidance specifically, this skill focuses on release-please-compatible conventions; for broader multi-repo git operations with submodules, defer to multi-repo-git-ops instead.
A specialized skill for generating high-quality illustrations for academic papers, supporting two output formats: (1) LaTeX/TikZ code: Suitable for structured diagrams such as system architecture diagrams, data flow diagrams, and geometric schematic diagrams, which can be directly embedded into papers; (2) draw.io XML: Suitable for highly decorative diagrams such as technical roadmaps, scientific research display diagrams, and academic presentation illustrations, supporting gradient colors, shadows, and free layout, which can be opened and edited at app.diagrams.net. Supports the above two output formats with a unified workflow: Analyze input (copy/image/paper) → Drawing instructions → Code generation → Compilation verification → Full-score delivery. It automatically identifies the field of the paper and designs illustrations as an expert in that field. Use when the user asks to: 画论文图、画架构图、画流程图、画示意图、 LaTeX画图、TikZ画图、论文配图、生成画图指令、复刻图片、 画图代码、学术论文图、画系统架构、画协议流程、论文插图、tikz diagram、 latex figure、根据论文画图、画个图、帮我画图、生成tikz、论文tikz、 根据文案画图、照着图片画、复刻这张图、技术路线图、科研架构图、 学术汇报图、drawio、draw.io、路线图、研究框架图、技术方案图。
Deploy OpenClaw AI agent platform on Alibaba Cloud ECS and integrate with DingTalk bot. OpenClaw (formerly Clawdbot/Moltbot, 中文名"龙虾") is an open-source AI assistant and automation platform supporting natural language-driven task automation with multi-channel chat integration. This Skill covers the full workflow from ECS instance creation, public network configuration, base environment setup, one-click OpenClaw deployment to DingTalk bot verification. End users can chat with the AI assistant by @mentioning the bot in a DingTalk group. Triggers: "OpenClaw", "龙虾", "Clawdbot", "Moltbot", "DingTalk bot", "DingTalk AI", "deploy OpenClaw on ECS", "AI agent platform", "DingTalk integration", "openclaw dingtalk", "openclaw deploy", "DingTalk AI employee", "Alibaba Cloud OpenClaw", "Bailian + DingTalk", "DingTalk group AI", "DingTalk smart assistant", "部署龙虾", "龙虾机器人", "龙虾钉钉"
Use when managing Alibaba Cloud Cloud Backup (HBR) via OpenAPI/SDK, including the user asks for backup lifecycle operations such as resource listing, policy/config updates, job status queries, and troubleshooting HBR backup or restore workflows.
Directa24 integration. Manage data, records, and automate workflows. Use when the user wants to interact with Directa24 data.
Guide post-trade compliance monitoring and trade surveillance system design. Use when building alert logic to detect churning, front-running, cherry-picking, layering, spoofing, wash trading, or marking the close, implementing post-trade best execution review, evaluating allocation fairness with pro-rata verification or dispersion analysis, designing exception-based monitoring workflows with escalation paths, correlating trading with MNPI events for insider trading detection, building personal trading surveillance for preclearance and blackout enforcement, determining SAR or blue sheet or CAT reporting triggers, or tuning surveillance thresholds to reduce false positives. Also covers turnover ratios, cost-to-equity ratios, and investigation case management.
Create image-based PowerPoint decks by (1) turning raw article content or notes into a detailed per-slide message plan when needed, (2) turning that message plan into a slide display plan and then a visual-production plan, (3) generating one 16:9 slide image per slide with all displayed text baked into the image (English by default; multilingual slide text supported), and (4) assembling an images-only .pptx that simply concatenates those images full-screen. Use when the user wants polished, consistent visuals with extensible style packs (cinematic dark, cinematic light, cinematic editorial, illustrative cinematic, animated feature, editorial, warm pastoral, tech, youth social, academic, corporate, whiteboard sketch), prefers not to hand-layout PPT objects, or wants a repeatable prompt workflow to iterate over time.