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Comprehensive framework for deep analysis of articles, papers, and long-form content using 10+ thinking models (SCQA, 5W2H, critical thinking, inversion, mental models, first principles, systems thinking, six thinking hats). Use when users want to: (1) deeply understand complex

Multi-agent parallel investigation for complex VCV Rack problems

Performs comprehensive, multi-layered research on any topic with structured analysis and synthesis of information from multiple sources.

Sub-agent powered code reviews spanning correctness, tests, consistency, and fit

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DeepChat app settings modification (DeepChat 设置/偏好) skill. Activate ONLY when the user explicitly asks to change DeepChat's own settings/preferences (e.g., theme, language, font size...). Do NOT activate for OS/system settings, editor settings, or other apps.

Molecular machine learning toolkit. Property prediction (ADMET, toxicity), GNNs (GCN, MPNN), MoleculeNet benchmarks, pretrained models, featurization, for drug discovery ML.

Diagnose and fix common Deepgram errors and issues.\nUse when troubleshooting Deepgram API errors, debugging transcription failures,\nor resolving integration issues.\nTrigger with phrases like \

Implement real-time streaming transcription with Deepgram.\nUse when building live transcription, voice interfaces,\nor real-time audio processing applications.\nTrigger with phrases like \

Optimize Deepgram costs and usage for budget-conscious deployments.\nUse when reducing transcription costs, implementing usage controls,\nor optimizing pricing tier utilization.\nTrigger with phrases like \

Implement audio data handling best practices for Deepgram integrations.\nUse when managing audio file storage, implementing data retention policies,\nor ensuring GDPR/HIPAA compliance for transcription data.\nTrigger with phrases like \

Collect Deepgram debug evidence for support and troubleshooting.\nUse when preparing support tickets, investigating issues,\nor collecting diagnostic information for Deepgram problems.\nTrigger with phrases like \

Deploy Deepgram integrations to production environments.\nUse when deploying to cloud platforms, configuring production infrastructure,\nor setting up Deepgram in containerized environments.\nTrigger with phrases like \

Create a minimal working Deepgram transcription example.\nUse when starting a new Deepgram integration, testing your setup,\nor learning basic Deepgram API patterns.\nTrigger with phrases like \

Install and configure Deepgram SDK/CLI authentication.\nUse when setting up a new Deepgram integration, configuring API keys,\nor initializing Deepgram in your project.\nTrigger with phrases like \

Deep dive into complex Deepgram migrations and provider transitions.\nUse when migrating from other transcription providers, planning large-scale\nmigrations, or implementing phased rollout strategies.\nTrigger with phrases like \

Set up comprehensive observability for Deepgram integrations with metrics, traces, and alerts.\nUse when implementing monitoring for Deepgram operations, setting up dashboards,\nor configuring alerting for Deepgram integration health.\nTrigger with phrases like \

Optimize Deepgram API performance for faster transcription and lower latency.\nUse when improving transcription speed, reducing latency,\nor optimizing audio processing pipelines.\nTrigger with phrases like \

Execute Deepgram production deployment checklist.\nUse when preparing for production launch, auditing production readiness,\nor verifying deployment configurations.\nTrigger with phrases like \

Apply production-ready Deepgram SDK patterns for TypeScript and Python.\nUse when implementing Deepgram integrations, refactoring SDK usage,\nor establishing team coding standards for Deepgram.\nTrigger with phrases like \

Plan and execute Deepgram SDK upgrades and migrations.\nUse when upgrading SDK versions, migrating to new API versions,\nor transitioning between Deepgram models.\nTrigger with phrases like \

Implement Deepgram callback and webhook handling for async transcription.\nUse when implementing callback URLs, processing async transcription results,\nor handling Deepgram event notifications.\nTrigger with phrases like \

Deep codebase initialization with hierarchical AGENTS.md documentation

AI-native OCR platform that turns documents into high-accuracy data in minutes. Using multi-model consensus, DeepRead achieves 95%+ accuracy and flags only uncertain fields for review—reducing manual work from 100% to 5-10%. Zero prompt engineering required.

Deep ReSearch Conversation is provided by Baidu for multi-round streaming conversations with \

Local-first deep research like OpenAI Deep Research: generates questions.md + response.md artifacts and enforces a time budget.

NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.

Query the DeepWiki MCP server for GitHub repository documentation, wiki structure, and AI-powered questions.

AI-powered Rust documentation generation engine for comprehensive codebase analysis, C4 architecture diagrams, and automated technical documentation. Use when Claude needs to analyze source code, understand software architecture, generate technical specs, or create professional

Comprehensive financial analysis using 60+ data endpoints. Analyze company fundamentals, financial statements, valuation metrics, profitability ratios, growth trends, and industry comparisons. Use for: (1) fundamental analysis and DCF modeling, (2) financial statement analysis,

Validate at every layer data passes through to make bugs impossible

Implement DeFi protocols with production-ready templates for staking, AMMs, governance, and lending systems. Use when building decentralized finance applications or smart contract protocols.

Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing

Check dependencies for known vulnerabilities using npm audit, pip-audit, etc. Use when package.json or requirements.txt changes, or before deployments. Alerts on vulnerable dependencies. Triggers on dependency file changes, deployment prep, security mentions.

You are a dependency security expert specializing in vulnerability scanning, license compliance, and supply chain security. Analyze project dependencies for known vulnerabilities, licensing issues, outdated packages, and provide actionable remediation strategies.

Map slice dependencies using DSM matrix and prioritize by risk

Guides dependency version updates by checking nuget.org for latest versions, triggering the dotnet-migrate-package Azure DevOps pipeline, and monitoring runs. Use this when asked to update external NuGet dependencies.

Smart dependency management for any language. Auto-detects project type, applies safe updates automatically, prompts for major versions, diagnoses and fixes dependency issues.

Manage major dependency version upgrades with compatibility analysis, staged rollout, and comprehensive testing. Use when upgrading framework versions, updating major dependencies, or managing breaking changes in libraries.

Deploy the Simba chat widget to a client website. Use when embedding the widget, connecting to Simba cloud or local, and configuring appearance.

Multi-step deployment agent for full-stack apps. Build → Test → GitHub → Cloudflare Pages with human approval at each step.

Deploy and serve web projects locally for preview. Automatically detects project type (Node.js or static HTML) and starts the appropriate development server.

Deploy this skill enables AI assistant to deploy machine learning models to production environments. it automates the deployment workflow, implements best practices for serving models, optimizes performance, and handles potential errors. use this skill when th... Use when

Deploys a VirtualMCPServer configuration locally for manual testing and verification

Guide for writing Aspire deployment end-to-end tests. Use this when asked to create, modify, or debug deployment E2E tests that deploy to Azure.

Expert deployment engineer specializing in modern CI/CD pipelines, GitOps workflows, and advanced deployment automation. Masters GitHub Actions, ArgoCD/Flux, progressive delivery, container security, and platform engineering. Handles zero-downtime deployments, security scanning,

Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.

Production deployment principles and decision-making. Safe deployment workflows, rollback strategies, and verification. Teaches thinking, not scripts.