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Found 9,865 Skills
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Kerberos, WinRM, SMB, RDP, Windows credential material, replayable tickets, delegation edges, and host-to-host pivot chains. Use when the user asks to replay Kerberos material, trace a WinRM, SMB, or RDP pivot, understand host-to-host privilege movement, or prove which Windows service accepted a credential or ticket. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for OAuth, OIDC, redirect flows, state or nonce handling, PKCE, token exchange, refresh logic, claim mapping, and accepted login paths. Use when the user asks to trace redirects, callback parameters, scopes, state, nonce, PKCE, refresh tokens, consent, or explain how an OAuth or OIDC chain turns into accepted identity or privilege. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Process and manage corporate actions from announcement through settlement. Use when handling dividends stock splits reverse splits mergers or spin-offs, managing voluntary elections for tender offers rights offerings or exchange offers, calculating record date and ex-date entitlements under current settlement cycles, building client notification workflows for upcoming corporate actions, collecting and submitting voluntary action elections to DTC or custodians, calculating fractional share handling or proration for reorganization events, adjusting cost basis and tax lots after corporate actions, reconciling expected entitlements against actual receipts, investigating missed or incorrectly processed corporate actions, or designing corporate action processing systems and controls.
Run sustainability pre-screening and audit workflows so plans meet environmental, social, governance, and funder-readiness standards.
Use when the user needs to turn a real software engineering / computer science project and an existing thesis draft into a submission-ready undergraduate thesis manuscript. Trigger for requests such as "根据项目把论文改成定稿", "按学校模板排版成最终版", "复制初稿后生成定稿 Word", "为定稿降查重", "根据PaperPass报告降AIGC", "继续在手改初稿上改", "恢复原来的图表和数据库说明", or when academic-paper-strategist has already produced an evidence-backed rewrite plan. Outputs a cleaned manuscript, final DOCX workflow, and a separate rework report.
Query SQLite, PostgreSQL, and MySQL databases and export results to CSV/JSON. Use when: (1) Extracting data for reports, (2) Database backup and migration, (3) Data analysis workflows, or (4) Automated database queries.
Feishu Message Sending and Document Creation Workflow. Trigger Scenarios: When users mention "send Feishu message", "Feishu document", "notify someone", "send to Feishu", "Feishu notification". Applicable to: Sending Feishu messages, creating Feishu documents, operating Feishu Base, managing Knowledge Base.
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for SSR, template rendering, route loaders, hydration payloads, server-client render boundaries, and template-to-handler enforcement gaps. Use when the user asks to inspect SSR or template routes, trace render context or hydration data, compare template gating with handler enforcement, explain preview or hidden-route rendering, or connect render pipeline behavior to the decisive branch. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Build, scaffold, extend, deploy, and troubleshoot event-driven AI agents and scheduled serverless agent apps on Azure Functions using azurefunctions-agents-runtime. Use when the user wants a scheduled agent, morning briefing, daily digest, timer agent, inbox summary, email or Teams briefing, background AI workflow, connector-triggered agent, event-driven AI automation, HTTP/chat agent, webhook-style agent, or Azure Functions hosted agent. Covers .agent.md, agents.config.yaml, Foundry gpt-4.1/gpt-5.x model choice, dynamic sessions for code execution and web browsing, built-in chat/API/MCP endpoints, remote MCP servers, Connector Namespaces, Office 365 or Teams MCP tools/triggers, custom Python tools, Agent Skills, azd deployment, local.settings.json, Application Insights, local development, and troubleshooting.
Development workflow, debugging, and troubleshooting for Electrobun desktop applications. This skill covers debugging the main process (Bun) and webview processes, Chrome DevTools integration, console logging strategies, error handling, performance profiling, memory leak detection, build error troubleshooting, common runtime errors, development environment setup, hot reload configuration, source maps, breakpoint debugging, network inspection, WebView debugging on different platforms, native module debugging, and systematic debugging approaches. Use when encountering build failures, runtime errors, crashes, performance issues, debugging RPC communication, inspecting webview DOM, profiling CPU/memory usage, troubleshooting platform-specific issues, or setting up development workflow. Triggers include "debug", "error", "crash", "troubleshoot", "DevTools", "inspect", "breakpoint", "profiling", "performance issue", "build error", "not working", or "logging".
Provides SonarQube and SonarCloud integration patterns via the Model Context Protocol (MCP) server. Enables quality gate monitoring, issue discovery and triaging, pre-push code analysis, and rule education directly in the agent workflow. Use when the user wants to check quality gates, search for Sonar issues, analyze code snippets before committing, or understand SonarQube rules. Triggers on "sonarqube", "sonarcloud", "quality gate", "sonar issues", "analyze with sonar", "check sonar", "sonar rule", "pre-push analysis".
Use when QA scope and strategy are defined and you need to generate detailed, executable test cases plus smoke, regression, and user acceptance suites tied to requirements, roles, workflows, and risks. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution. Explicit full or end-to-end spec refinement requests continue through the existing 18-stage refinement cascade.