AI/ML plugins

Orchestrate 1,388 specialized AI skills in Claude Code to automate expert workflows for Azure SDK integrations, Odoo/Shopify configs, SEO audits, security pentests, full-stack scaffolding, agent building, and DevOps pipelines across Python, React, AWS, Kubernetes.

Search, retrieve, improve, and manage thousands of AI prompts and Claude skills from prompts.chat directly in your coding assistant. Install skills to extend capabilities, fill prompt variables, save custom prompts with metadata, and enhance them using AI.

Generate investor-ready startup business analyses: calculate TAM/SAM/SOM market sizing, build 3-5 year financial models with cohort revenue, cash flow, burn rate, and scenarios; analyze competitive landscapes and team structures; benchmark metrics like CAC/LTV and ARR; produce full business case documents.

Orchestrate swarms of AI agents for complex multi-step tasks using SPARC methodology, swarm coordination, and GitHub automation, with WASM-accelerated local execution and a cloud-based orchestration platform providing 70+ tools.

Refactors and modernizes legacy codebases by detecting code smells, SOLID violations, and technical debt, generating prioritized remediation plans with cost estimates, while preserving project context for safe incremental migrations.

Orchestrate swarms of specialized AI agents to automate end-to-end software development: plan features, implement code with Rails/Python/TS patterns, conduct multi-perspective reviews for architecture/security/performance, resolve todos/PR feedback in parallel, run browser/iOS tests, sync Figma designs, generate docs/videos, and ship PRs.

Build and deploy production-grade LLM applications with LangGraph for agent orchestration, advanced RAG pipelines leveraging vector and hybrid search, prompt engineering patterns, and automated evaluation. Covers embedding model selection, vector index optimization, and multi-agent architectures for document Q&A, chatbots, and semantic search over proprietary data.

Delegate architecture, implementation, optimization, and debugging of complex applications to specialized AI agents expert in Python/Django/FastAPI, TypeScript/React/Next.js/Angular/Vue, Go, Rust, Java/Spring Boot, PHP/Laravel/Symfony, C#/.NET, mobile (Flutter/React Native/Swift/Kotlin), Elixir/Rails, SQL, and DevOps tools.

Perform end-to-end research workflows: market analysis, competitor benchmarking, trend detection, data validation, and idea vetting. A team of specialized agents retrieves and synthesizes information from web, files, and scientific literature to deliver actionable insights and strategic recommendations.

Build production-ready data pipelines with Apache Airflow and dbt, manage scalable data warehouses, and implement vector search and RAG systems using embedding models and vector databases.

Build and evaluate production-grade AI agents using LangGraph, RAG systems, MCP servers, and prompt engineering patterns—with behavioral testing and reliability monitoring.

Automate multi-platform workflows across Airtable, Google Sheets, Notion, Slack, and Make (Integromat) using Composio-connected tools, with guidance on building MCP servers and orchestrating durable execution on n8n, Temporal, or AWS Step Functions.

Delegate complex coding tasks and adversarial code reviews to Codex CLI from within Claude Code, with background job support, git-scoped analysis, and result retrieval.

Build, deploy, and monitor AI-powered cloud applications on Azure using containerized apps, serverless functions, OpenAI integration, AI Search, and observability across .NET, Python, and Node.js.

Accelerate LLM application development with production-ready patterns for context window management, RAG pipelines, prompt caching, observability via Langfuse, and agent architectures.

Coordinate specialized AI agents through the full academic paper writing workflow: from literature search and argument blueprinting to drafting, citation verification, bilingual abstract generation, journal formatting, and simulated peer review, producing publication-ready LaTeX, DOCX, or PDF output.

Delegate complex data engineering, ML, and AI workflows to specialized sub-agents that design scalable pipelines, build and optimize models, architect LLM systems, tune databases for performance, and deploy production infrastructure across clouds.

Upgrade Claude AI integrations by migrating code, prompts, and API calls from Sonnet 4.0/4.5 or Opus 4.1 to Opus 4.5, automatically updating model strings across Anthropic, AWS Bedrock, GCP Vertex AI, and Azure AI Studio platforms.

Orchestrate creative AI image generation workflows: search a 1300+ curated design gallery for inspirations, craft batch prompts for parallel variations and concepts, auto-enhance short prompts, and generate images via MeiGen server with ComfyUI or OpenAI-compatible APIs.

Generate Product Requirements Documents (PRDs) interactively by answering questions on feature goals, users, and scope, structuring them into user stories with acceptance criteria and non-goals, then convert to prd.json format for autonomous execution by the Ralph agent system.

Invoke MiniMax AI skills to scaffold React/Next.js frontends, fullstack apps with Node/Python/Go backends, Flutter/React Native/Android/iOS mobile projects; generate/edit DOCX/PDF/PPTX/XLSX files; produce GIF stickers, shaders, music playlists/videos; analyze images via CLI workflows.

Manage the full ML lifecycle on Hugging Face Hub: search and select models, train or fine-tune with TRL/Unsloth, evaluate locally, build and deploy Gradio demos on Spaces, publish research papers, and monitor training metrics — all from the command line or agent.

Scaffold new Claude Agent SDK apps in TypeScript or Python by interactively gathering requirements, installing dependencies, and configuring projects. Verify apps post-creation or changes for SDK best practices, code quality, security, type safety, documentation, and deployment readiness.

Build and integrate AI copilot features into web apps using CopilotKit v2, with full support for chat interfaces, agent-to-frontend communication, multiple agent frameworks, and runtime setup in React, Next.js, and other JS frameworks

Orchestrate multi-agent teams for complex AI-driven projects: decompose tasks, match capabilities, coordinate workflows, manage shared context and errors, distribute workloads, monitor performance with Prometheus and OpenTelemetry, and synthesize insights from interactions. Integrates PowerShell, .NET, Azure ops via specialist subagents.

Solve IMO, Putnam, USAMO, and AIME competition math problems using pure reasoning enhanced by adversarial verification that detects self-check errors missed by standard methods. Obtain calibrated confidence scores and PDF outputs for verified solutions.

Automate private equity workflows: screen deals, run due diligence, analyze financials, build IRR models, assess unit economics, monitor portfolio performance, and generate investment memos and value creation plans.

Persist memory across AI coding agent sessions by capturing tool usage and insights, compressing via LLM, and injecting relevant past context into future interactions. Recall session history, search observations, and forget specific data via natural language commands.

Evaluate and improve LLM applications by instrumenting agents, chatbots, and RAG pipelines with DeepEval tracing, generating test suites, running evaluations, and exporting traces to Confident AI for observability and iterative refinement.

Build, validate, and debug n8n workflows with AI-guided skills for JavaScript/Python code nodes, LangChain AI agents, binary data handling, error recovery, sub-workflow composition, and architectural patterns, enforced by a hooks layer that prevents production breakage during MCP tool calls.

Accelerate early-stage life sciences R&D by connecting to preclinical research tools and databases for literature search, genomics analysis, target prioritization, and data conversion.

Delegate full-stack development workflows to Claude via 213 specialized agents, commands, and skills: refactor code, generate tests/deployments/Dockerfiles/K8s manifests, audit security/performance, document APIs/onboarding, orchestrate Git ops, and apply patterns across JS/TS/Python/Rust/Go/Java stacks.

Spawn parallel AI subagents in isolated git worktrees to compete on tasks like code optimization, refactoring, test writing, or bug fixing. Evaluate results using pytest metrics or LLM judging on git diffs, rank agents, and merge the top performer into your base branch.

Perform AI-powered code reviews on GitHub and GitLab pull requests by connecting to Greptile API. View and resolve review comments directly within Claude Code. Query indexed repositories for code search, codebase Q&A, and context retrieval to accelerate development workflows.

Launch GPU/TPU clusters, training jobs, and inference servers across 25+ clouds using SkyPilot. Deploy to Kubernetes pods and Slurm jobs; debug YAML configs and optimize costs in your AI workflow.

Perform product market research workflows: generate user personas, behavioral segments, and customer journey maps from surveys, CSVs, or feedback; conduct competitive landscape analysis with competitor profiles and differentiation maps; run sentiment analysis on reviews for insights and recommendations; estimate TAM/SAM/SOM with growth projections; output markdown reports.

Build AI agents that generate and interact with React UI components using Tambo: auto-integrate into existing React/Next.js/Vite apps by detecting stack, installing packages, wiring providers, and adding chat UI; or CLI-scaffold new generative UI apps with starter components and schemas.

Look up Python code examples and enforce Pythonic style — fetch syntax, concurrency, ML, and HPC references from pythonsheets.com while writing, debugging, or optimizing code, and get linting guidance for readable, idiomatic Python.

Generate and edit images using GPT Image 2 and OpenAI-compatible endpoints with 70+ structured prompt templates across 18 categories, plus build polished visual web artifacts like pages, dashboards, prototypes, slide decks, and data visualizations using HTML/CSS/JavaScript/React.

Direct AI coding agents to create or update promptfoo evaluation suites with configs, prompts, tests, deterministic assertions, and provider setups following best practices. Streamline LLM eval coverage, regression debugging, and new eval matrix generation in JavaScript or Python projects using OpenAI or Anthropic models.

Semi-automated research assistant for academic ML/AI research and software development, enabling literature review with Zotero integration, paper writing with Nature/NeurIPS templates, experiment analysis with statistical validation, and Obsidian-based project knowledge management, plus code quality enforcement and CI workflows.

Invoke /deploy to initiate TensorZero deployment workflow, which prompts plugin upgrade before unlocking full deployment capabilities for AI/ML applications.

Automate long-form webnovel creation: initialize projects interactively with genre/characters/worldbuilding/outlines, generate beat sheets/chapters (2000+ words), extract entities/relationships to SQLite indexes, visualize status/entity graphs in read-only dashboard, recover interrupted workflows, and validate chapters via agents for inconsistencies, pacing, OOC, reader pull, and quality reports.

Run 10 AI agents to fully automate Obsidian vault management: triage Gmail/Hey emails and inbox notes, extract deadlines from Google Calendar, transcribe audio into structured notes, audit and defragment vault structure, generate weekly agendas, evolve knowledge graph, and handle multilingual inputs.

Orchestrate structured, spec-driven development workflows for AI coding agents — from project initialization and phased planning through autonomous execution, code review, testing, and milestone tracking. Includes context engineering, knowledge graphs, and multi-agent debugging.

Leverage Common Room's product usage, engagement, and intent signals as a GTM copilot to research accounts and contacts, generate call prep briefs with talking points and objections, draft personalized email/LinkedIn/call outreach, build targeted prospect lists, produce weekly meeting briefings, and create strategic account plans.

Run institutional-grade equity research on A/HK/US stocks with deep fundamental analysis, 65-investor panel voting, pump-and-dump fraud detection, DCF/comps/LBO valuation, portfolio attribution, and Bloomberg-style HTML reports.

Quickly pack local or remote GitHub repositories into AI-optimized formats (XML, Markdown, JSON, plain) with compression, file filters, git diffs/logs, and clipboard copy using simple slash commands.

Generate, edit, and inpaint images via GPT Image 2 CLI skill, using a reference prompt gallery to match styles for UI mockups, diagrams, posters, research figures, anime, and Chinese typography workflows.

Build and orchestrate advanced Claude Code agentic workflows by creating meta-prompts, subagents, hooks, MCP servers, slash commands, and skills; execute hierarchical plans, run autonomous coding loops, apply expert debugging and productivity frameworks like 5 Whys or Eisenhower Matrix, and audit components for compliance and quality.

Debug and fine-tune language models using the Tinker API: diagnose training pipeline issues, replicate research papers, run RL/SFT/DPO experiments, and monitor training logs—all from the command line.

Govern AI use across the firm: triage use cases against your registry, run impact assessments under relevant regimes, review vendor AI terms for training-data and liability gaps, and keep policies current with automated drift detection and regulatory gap analysis.

Track real-time prices for cryptocurrencies, stocks, forex, and commodities from multiple exchange APIs and WebSockets. Set watchlists and alerts, export data to CSV/JSON, analyze trends with technical indicators, volume, patterns, and generate trading signals, forecasts, and recommendations.

Build and configure neural network architectures like CNNs and RNNs for ML tasks such as image classification and text generation. Generate PyTorch code with validation and error handling, get metrics and insights, save artifacts, and produce documentation.

Scaffold, develop, evaluate, deploy, and monitor AI agents using Google ADK (Agent Development Kit). Manage the full agent lifecycle from project scaffolding to production deployment on GCP with CI/CD, infrastructure as code, and observability.

Generate AI videos from text prompts or images using Kling AI API in Python. Build scalable production pipelines with async Redis queues, batch processing, rate limiting, webhooks, monitoring, cost controls, content filters, security audits, cloud storage uploads, and CI/CD integration.

Integrate Perplexity Sonar API for AI-powered web search with verifiable citations into Node.js/Python apps. Handle full lifecycle workflows: auth setup, error debugging, rate limiting, caching optimization, monitoring, security guardrails, CI/CD testing, and scalable deployments to Vercel/Docker.

Orchestrate multi-agent AI systems with AI SDK v5 for task decomposition, handoffs, routing, and coordination across OpenAI, Anthropic, and Google providers. Use commands to initialize projects, generate specialized agents with custom prompts and tools, test workflows with metrics, and deploy orchestrator agents for complex task handling in TypeScript.

Run end-to-end YouTube content strategy workflows: research competitors via channel scraping and analysis, generate tiered video ideas with validation, produce structured briefs and detailed outlines including demo prep, craft CTR-optimized titles and thumbnail concepts.

Automate training and optimization of ML models for classification and regression on datasets: analyze data, select/configure algorithms, cross-validate, evaluate metrics, generate Python code using scikit-learn/PyTorch/TensorFlow/XGBoost, and save artifacts.

Set up Ollama for local AI model inference on macOS, Linux, or Docker with automated installation, hardware-optimized model selection, GPU configuration, verification, model pulls, API testing, and client integration via Python, Node.js, or REST for zero-cost, privacy-first LLM workflows.

Detect and rewrite AI-generated Korean text to sound human-written, using a multi-phase pipeline that scans for 40+ AI-typical patterns across 10 categories, preserves content, and validates semantic equivalence.

Write Markdown contracts (.prose.md) that orchestrate multi-agent AI workflows, compile and validate them, then execute them in a virtual machine with session, parallel, loop, and conditional support — all with an auditable trace.

Manage Google Ads and Meta Ads campaigns, run SEO audits, optimize content for AI search engines (GEO), and generate schema markup — all from Claude. Includes keyword research, broken link scanning, landing page scoring, and content calendar planning powered by Google Search Console and advertising APIs.

Automate spec-driven development workflows with AI agents that handle GitHub issue fixing, PR review, deep research, image generation, and session analysis. Includes custom slash commands, skill creation, and browser automation via Chrome DevTools Protocol.

Build production-grade LLM gateways with OpenRouter: route requests across 400+ models by task or criteria, chain fallbacks for reliability, cache responses to cut costs/latency, monitor usage/costs/latency, redact PII for compliance, and benchmark performance using Python OpenAI SDK wrappers.

Generate production-ready Google Cloud code examples, starter kits, and templates for AI agents and apps from official ADK, Genkit, and Vertex AI sources. Adapt to Python, TypeScript, or Go with security, monitoring, Firebase, and Terraform IaC integration.

Track real-time crypto derivatives markets—futures, options, perpetuals—with funding rates, open interest, liquidations, IV, Greeks, and basis across Binance, Bybit, Deribit using Python CLI tools, and use an AI agent to analyze data and generate trading signals.

Integrate Speak AI SDK into language learning apps: scaffold conversations and pronunciation assessments with real-time feedback, configure auth/security/compliance, deploy to Vercel/GCP/Docker with CI/CD, optimize costs/performance/rate limits, monitor metrics, and troubleshoot via diagnostics/runbooks.

Persistent memory for AI coding agents that survives across sessions and compactions, letting you save decisions, conventions, bugs, and discoveries so agents retain context indefinitely without relying on API keys or external services.

Build, debug, optimize, secure, and deploy FireCrawl web scraping pipelines for LLM/RAG data ingestion: scrape/crawl sites to markdown/JSON, extract structured data, handle rate limits/errors, add monitoring/observability, scale with backoff/caching, and integrate into Node/Python apps from dev to production.

Aggregate cryptocurrency news from 50+ RSS sources with coin, category, and time filters, relevance scoring, AI sentiment analysis, trend detection, and market impact scoring to monitor market updates, announcements, and gain real-time trading insights.

Automate machine learning feature engineering by generating and executing validated Python code to create interactions, scale data, encode categoricals, select features via importance analysis, compute metrics, save artifacts, and generate documentation.

Generate and execute automated Python pipelines for data cleaning, transformation, validation, and ETL in ML workflows. Analyze context to produce AI/ML code with built-in validation, error handling, performance metrics, saved artifacts, and documentation.

Generate plots, charts, and graphs from data via natural language requests—AI analyzes datasets, selects optimal visualization types, produces validated Python code, delivers performance metrics and insights, saves artifacts, and creates documentation.

Automate full Databricks lakehouse lifecycle: build Delta Lake ETL pipelines with medallion architecture and Auto Loader, engineer ML workflows via MLflow and Feature Store, deploy jobs/pipelines with Asset Bundles and GitHub Actions CI/CD, secure via Unity Catalog RBAC, optimize costs/performance, troubleshoot errors, and monitor with system tables.

Generate and run Python code to analyze images via computer vision, performing object detection, classification, and segmentation. Handles validation, errors, performance metrics, saves outputs as artifacts, and adds documentation. Trigger with 'analyze image' prompts or process-vision command.

Optimize LLM prompts for OpenAI and Anthropic by automatically detecting redundancy, simplifying instructions, and rewriting to reduce token usage, lower costs, and improve performance.

Set up OpenRAG locally by assessing your environment, generating requirements and Docker/uvx configs, and verifying services at localhost:3000 and :5001/docs. Then integrate its SDK into Python or JavaScript/TypeScript apps via pip/npm/uv/yarn, configure env vars/API keys, and implement chat/search clients with code examples.

Accelerate Atomic Agents app development through a guided 7-phase workflow: delegate schema design, agent and tool creation, architecture planning, codebase analysis, and code review to specialized AI sub-agents for scalable multi-agent LLM systems.

Integrate OpenEvidence medical AI for clinical decision support in healthcare SaaS: run evidence-based queries, drug interactions, DeepConsult syntheses; automate auth setup, rate limiting, caching, RBAC, monitoring, CI/CD pipelines, Docker deploys, and production checklists in TypeScript/Node.js/Python projects.

Build production Python applications on Azure using SDK best practices for AI agents and ML pipelines, content analysis and multimodal processing, vector/hybrid search, hierarchical storage and queues, event streaming with Event Hubs and Service Bus, OpenTelemetry monitoring, secure authentication and key management, plus infrastructure provisioning.

Synthesise multi-source user signals into weighted insight briefs with confidence ratings, design and evaluate A/B experiments with statistical rigor, structure AI/ML product decisions on a canvas, conduct ethical reviews of AI features with risk scoring, and transform feature briefs into ready-to-use design handoff docs for designers

Perform NLP analysis on text, code, or data to detect sentiment, extract keywords and named entities, and model topics. Generate production-ready AI/ML code from natural language requirements, complete with validation, error handling, performance metrics, insights, artifacts, and documentation.

Access Z.AI's multimodal AI capabilities directly from your CLI to analyze images and videos with vision models, perform OCR and UI-to-code conversion, search the web, extract pages as markdown, and explore GitHub repositories deeply. Requires Z_AI_API_KEY for seamless terminal-based workflows.

Build and evaluate supervised classification models from labeled data for tasks like spam detection or churn prediction. Generates complete Python code including training, validation, error handling, performance metrics, artifacts, and documentation.

Forecast future values from historical time series data using ARIMA and Prophet models, including trend, seasonality, and autocorrelation analysis with confidence intervals. Generate validated AI/ML code for forecasting tasks complete with error handling, performance metrics, insights, artifacts, and documentation.

Validate AI/ML models and datasets for bias, fairness, and ethics using Fairlearn, AIF360 metrics, four-fifths rule, and severity classification. Generate production-ready AI/ML code with integrated validation, error handling, metrics, artifacts, and documentation tailored to modern frameworks.

Evaluate machine learning models using metrics like accuracy, precision, recall, and F1-score to perform performance analysis, validation, model comparison, and optimization. Generate production-ready AI/ML code that includes validation, error handling, performance metrics, saved artifacts, and documentation.

Generate importable n8n workflow JSON files from natural language descriptions, designing complex automations with loops, branching, error handling, retries, notifications, AI content pipelines, lead qualification, document processing, and OpenAI/JavaScript integrations.

Create and validate production-grade Claude Code skills per AgentSkills.io 2026 spec and 100-point rubric, plus Anthropic agent .md files matching 16-field 2026 standard. Audit existing skills/agents or build custom subagents for orchestrators and marketplace submission.

Design, implement, and deploy secure Firebase apps with Vertex AI Gemini integration in Cloud Functions for authentication, Firestore, storage, and hosting.

Fetch OpenSea NFT metadata to compute rarity scores using algorithms like rarity_score or entropy, rank individual tokens, compare collections, and generate markdown reports with trait breakdowns, valuation estimates, and market insights.

Engineer production-ready ADK agents and multi-agent systems in Python, Java, or Go, generating clean code structures, unit tests, safe tools, and deployment automation for Vertex AI.

Integrate Deepgram speech-to-text SDK into Node.js, TypeScript, or Python apps with production workflows for real-time streaming transcription, batch processing, diarization, cost optimization, security hardening, RBAC, Docker/Kubernetes deployment, CI/CD, monitoring, and migrations from AWS Transcribe or OpenAI Whisper.

Deploy and orchestrate production multi-agent systems on Vertex AI using ADK and A2A protocol: discover agent capabilities via AgentCard, submit tasks with JSON-RPC over HTTP, manage sessions and code execution sandboxes, share state via Memory Bank, poll status, and retrieve results with artifacts.