AI agents are easy to demo, but getting them to work in real use is a different challenge.
Many setups can give good answers. Very few can finish a task, deal with errors, and keep track of what is going on across steps. To build that kind of agent, you need the right skills, such as using tools, managing memory, handling data, deploying your setup, and shaping how people use it.
This article covers the top 10 skills you need to build AI agents that actually work outside demos. Let’s get started!
1. Tool Integration with Composio
Composio helps your agent connect to external tools and APIs without dealing with complex setup. You can plug your agent into 1000+ tools like Gmail, Slack, GitHub, and more, and start executing real actions quickly.
Composio’s skill pack is built from real production use. It handles things that most agents get wrong, such as tool routing, session handling, authentication, and real-time events.
What the agent learns:
- Tool Routing: Picking the right tool at the right time with proper session control
- Authentication Flows: OAuth, API keys, auto vs manual auth, and connection handling
- Session Management: Keeping user data isolated across multi-user setups
- Webhook And Trigger Handling: Creating triggers, verifying requests, and managing lifecycle
- Framework Integration: Working with LangChain, OpenAI Agents SDK, CrewAI, and Claude
Why it matters:
Without this skill, agents often mix up user sessions, break authentication, or call tools out of order. These issues may not show up in testing, but they cause serious failures in real use.
Install:
npx skills add composiohq/skills
This is the layer that turns your agent from a chatbot into a system that can actually get work done.
2. Frontend And Deployment Skills with Vercel
Vercel’s agent skills focus on building and deploying fast web apps using React and Next.js. It covers performance, UX, accessibility, and deployment best practices. This is a core skill set for any agent working on frontend or full-stack projects.
What the agent learns:
- React And Next.js Performance: 40+ rules across multiple areas, from fixing render waterfalls to better caching patterns
- Bundle Optimization: Reducing bundle size, using dynamic imports, and avoiding unnecessary client components
- Server and Client Boundary: Sending only required data across components and avoiding over-serialization
Why it matters:
Frontend is where most agent-generated code breaks first. Code may work locally but fail in real-world use due to slow load times, poor structure, or bad UX. Without this skill, agents create apps that feel slow and unstable at scale.
Install:
npx skills add vercel-labs/agent-skills
3. Memory And Retrieval Skills with Weaviate
The Weaviate agent skill pack connects your agent to Weaviate’s infrastructure and fixes a common issue where agents guess outdated syntax or misuse search settings. It helps your agent build reliable semantic search and retrieval systems without errors.
What the agent learns:
- Cluster Management: Inspecting schemas, creating collections, and managing metadata
- Data Lifecycle: Importing and structuring CSV, JSON, and JSONL data with clean pipelines
- Semantic Search: Choosing between keyword, semantic, and hybrid search with correct tuning
- Agentic Search: Using natural language queries with built-in search and citation support
- Advanced Retrieval: Working with multivector embeddings and combining BM25 with vector search
- End-to-End Cookbooks: Building full RAG pipelines, chat systems, and deployable services
Why it matters:
Without this skill, agents often use outdated syntax, break search queries, or miss key setup steps. With it, an agent can set up a working search system, load data, and build a usable retrieval pipeline in minutes.
Install:
npx skills add weaviate/agent-skills
4. Model And ML Workflow Skills with Hugging Face
The Hugging Face agent skill pack connects your agent to the full Hugging Face ecosystem. It supports tools like Claude Code, Codex, Gemini CLI, and Cursor, and covers the complete ML workflow from datasets to training to deployment.
What the agent learns:
- HF CLI: Managing models, datasets, repositories, and authentication using tokens
- Dataset Workflows: Fetching data, filtering, searching, and downloading structured datasets
- Model Training: Fine-tuning with SFT, DPO, GRPO, reward models, and handling deployment formats like GGUF
- Gradio UIs: Building demos, chat interfaces, and interactive web apps
- HF Jobs: Running GPU workloads, batch jobs, and tracking experiments
- Transformers.js: Running models directly in the browser
- Paper Publishing: Managing and linking research papers with models and datasets
Why it matters:
ML workflows include many connected steps where small mistakes can break results. Issues like wrong configs, poor batching, or missed auth steps can affect training and output quality. This skill helps agents follow correct patterns and produce reliable results across the workflow.
Install:
npx skills add huggingface/skills
5. Web Data And Automation Skills with Olostep
Olostep is a web scraping, crawling, and search API built for AI workflows. The Olostep setup works through MCP, so you can plug it into any MCP-compatible agent and grant it access to real-time web data.
What the agent learns:
- Single URL Scraping: Extracting content from any page in Markdown, HTML, JSON, or plain text with JavaScript support
- Batch Extraction: Processing up to 100,000 URLs in parallel with structured outputs
- Site Crawling: Moving across pages to collect data from full websites
- Structured Parsers: Using ready-made extractors for sources like Amazon, Google Search, and Maps
- Natural Language Extraction: Asking for data in plain English and getting structured results
- Web Agents: Automating steps like form filling, clicking, and navigation
Why it matters:
Web data is messy, inconsistent, and often blocked. Agents that try to scrape on their own spend time on retries, broken parsing, and access issues. Olostep handles these problems and returns clean, usable data in a single step.
6. Infrastructure And Edge Skills with Cloudflare
The Cloudflare agent skill pack covers a full platform for building, deploying, and running applications at the edge. It includes compute, storage, AI tools, networking, and security, all in one place. Skills load based on what your agent is working on, so there is no manual setup.
What the agent learns:
- Workers And Pages: Deploying serverless functions and static sites with proper configs, routes, and secrets
- Storage: Using KV, D1, and R2 based on the type of data and access pattern
- Durable Objects: Managing stateful logic, coordination, and real-time features with WebSockets and storage
- AI On The Edge: Running inference, vector search, and building stateful agents with built-in tools
- MCP Server Creation: Creating remote MCP servers with tool access and OAuth support
- Performance: Improving load times, caching responses, and fixing render-blocking issues
- Security: Setting up WAF, handling DDoS protection, and applying Zero Trust patterns
Why it matters:
Cloudflare has many moving parts and strict runtime rules. Agents often use unsupported APIs, misconfigure storage, or deploy incorrectly. This skill helps the agent follow correct patterns and build systems that run reliably at the edge.
Install:
npx skills add cloudflare/skills
7. Monitoring And Debugging Skills with Sentry
The Sentry agent skill pack is based on real patterns used by the Sentry engineering team. It is not basic documentation. It reflects how production systems are monitored, debugged, and maintained at scale.
What the agent learns:
- AGENTS.md Generation: Creating and updating agent docs that match real project structure
- Claude Settings Auditing: Checking configs early to catch issues before they reach production
- Sentry SDK Integration: Setting up error tracking, DSNs, source maps, and capturing useful context
- Error Triage Patterns: Managing issues, grouping errors, setting alerts, and tracking releases
- Observability For Agents: Making workflows traceable and easy to debug with distributed tracing
Why it matters:
Agents that ship code without monitoring create failures that are hard to detect and fix. This skill ensures your agent sets up tracking from the start, so errors are visible and easier to debug in real use.
Install:
npx skills add getsentry/skills
8. Backend And Database Skills with Supabase
The Supabase agent skill pack teaches your agent how to work with a full backend platform built on Postgres. It covers database, auth, storage, real-time features, and serverless functions. It is widely used in modern full-stack apps.
What the agent learns:
- Postgres Best Practices: Writing efficient queries, using indexes, and avoiding slow patterns
- Row Level Security: Defining access rules correctly to protect user data
- Auth Patterns: Managing sessions, JWTs, OAuth, and protected routes
- Storage: Handling file uploads, access control, and signed URLs
- Edge Functions: Deploying serverless logic with proper configs and secrets
- Realtime: Subscribing to changes, tracking presence, and managing connections
- Client Libraries: Using Supabase SDKs with proper typing and error handling
Why it matters:
Supabase is used in many production apps, but small mistakes can cause serious issues. Poor queries can slow systems down, and incorrect access rules can expose data. This skill helps your agent follow correct patterns for both performance and security.
Install:
npx skills add supabase/skills
9. Payments And Billing Skills with Stripe
The Stripe agent skill pack teaches your agent how to build secure payment flows, manage subscriptions, and handle billing systems correctly. It covers the full lifecycle of payments and helps avoid costly mistakes.
What the agent learns:
- Payment Intents: Creating and confirming payments, handling authentication flows, and avoiding duplicate charges
- Subscriptions And Billing: Managing recurring payments, plan changes, trials, and cancellations
- Webhook Handling: Verifying signatures, handling retries, and processing events in the correct order
- Connect And Payouts: Routing payments in marketplace setups and handling transfers
- Fraud Detection: Using risk signals and rules to prevent fraud without blocking valid users
- Test Mode Patterns: Simulating real payment scenarios and testing failure cases
- Error Handling: Managing declines, network issues, and retries without breaking the flow
Why it matters:
Payments are a critical part of any product. Small mistakes can lead to failed transactions, duplicate charges, or broken billing flows. This skill helps your agent follow safe and reliable patterns from the start.
Install:
npx skills add stripe/agent-toolkit
10. Video And Media Generation Skills with Remotion
The Remotion agent skill pack teaches your agent how to create videos using code. It uses React to build, structure, and render videos, which opens up a new type of output that most agents cannot handle.
What the agent learns:
- Composition Model: Structuring videos using React components, sequences, and layouts
- Timeline API: Controlling animation with frame-based logic and timing functions
- Rendering Pipeline: Generating videos in formats like MP4, WebM, and GIF using the CLI
- Audio And Video Assets: Adding and syncing audio, clips, and visual elements
- Dynamic Content: Creating videos that change based on data or inputs
- Walkthrough Generation: Producing product demos and app walkthrough videos from UI flows
Why it matters:
Video creation has mostly been manual and tool-heavy. This skill allows your agent to generate videos directly from code, enabling automation of content such as demos, reports, and visual stories.
Install:
npx skills add remotion-dev/remotion
Conclusion
The agent skills ecosystem is moving fast. Fine-tuning changes how an AI behaves and is costly to maintain. Agent skills are simple instruction files. You can update, swap, or share them at any time without changing the model.
Each skill pack in this list carries real engineering knowledge. It includes production patterns, lessons from real systems, and platform-specific practices, all in a form an agent can use right away.
Install the ones that match your stack. Your agents will spend less time making errors and more time getting work done.
