Automation

This tutorial demonstrates building a webhook-triggered SRE incident response agent using Claude Managed Agents that automatically investigates production alerts, consults runbooks, proposes infrastructure fixes via pull requests, and gates merging behind human approval. The agent combines built-in sandbox tools (bash, read, edit) with custom tools for PR management and human-in-the-loop approval, providing complete audit trails in the Anthropic Console. The example uses mocked PagerDuty, GitHub, and Datadog integrations to focus on agent patterns, with guidance for swapping in real services.

This cookbook demonstrates building a Slack data analyst bot using Claude Managed Agents and Bolt for Python. Users mention the bot with a CSV file to receive narrative analysis reports in-thread, with support for multi-turn follow-ups within the same session. The implementation handles file uploads, streams agent progress updates, and manages session persistence across Slack threads.

This cookbook demonstrates building a Claude-powered threat intelligence enrichment agent that autonomously investigates Indicators of Compromise (IOCs) by querying multiple threat intel sources, correlating findings, mapping to MITRE ATT&CK, and generating structured reports for SIEM/SOAR integration. The agent uses Claude's tool-use capabilities to decide which intelligence sources to query, chain tool calls based on discoveries, and convert free-text analysis into analyst-ready JSON reports. The architecture uses simulated threat intel backends that can be swapped with real APIs (VirusTotal, AbuseIPDB, Shodan, etc.) without changing orchestration logic.

Canary is an AI QA agent that analyzes pull requests by understanding codebases, identifying affected user workflows, and automatically generating and executing end-to-end tests. The platform connects to repositories, reads diffs to understand intent, runs tests against preview apps, and reports results directly on PRs with recordings. Beyond PR testing, it supports regression suites and continuous testing via plain English prompts, addressing the gap where modern AI tools accelerate development but lack comprehensive real-world behavior testing before merge.

This cookbook demonstrates how to connect Claude agents to external systems using MCP (Model Context Protocol) servers for GitHub monitoring and CI workflows. The guide covers integrating Git and GitHub MCP servers to enable agents to interact with repositories, manage workflows, and perform observability tasks. By leveraging MCP servers, agents gain access to specialized tools for Git operations, GitHub platform integration, and CI/CD monitoring without relying on command-line interfaces.

This cookbook teaches how to build a research agent using Claude Agent SDK with WebSearch tool for autonomous information gathering and synthesis. The guide demonstrates creating a functional research agent in just a few lines of code, then progresses to production improvements including conversation memory, system prompts for specialized behavior, and multimodal research capabilities. The agent autonomously decides when and how to search, follows promising leads, and synthesizes findings without predefined workflows.

This cookbook teaches how to build financial dashboards, portfolio analytics, and automated reporting workflows using Claude's Excel, PowerPoint, and PDF skills. It covers three main use cases: creating comprehensive financial models with formulas and charts in Excel, generating executive presentations from financial data, and automating multi-format reporting pipelines. The guide includes setup instructions, data loading examples, and helper functions for working with the Anthropic SDK to create professional financial documents directly through Claude's interface.

This cookbook demonstrates building an autonomous SRE incident response agent using the Claude Agent SDK with read-write MCP tools for safe infrastructure access. The agent can investigate incidents by querying metrics and logs, diagnose root causes, apply remediations by editing configs and restarting services, and document post-mortems. The pattern uses a subprocess-based MCP server with scoped tool access, clear tool descriptions, and human-in-the-loop workflows to enable autonomous yet controlled incident response.

This guide introduces Claude Skills, specialized capability packages that enable document creation, data analysis, and workflow automation through Excel, PowerPoint, and PDF generation. Skills use a three-tier progressive loading model (metadata → full instructions → linked files) to optimize token usage and efficiency. The tutorial covers environment setup, API configuration, skill discovery, and practical quick-start examples for Excel, PowerPoint, and PDF workflows.

Programmatic Tool Calling (PTC) enables Claude to write and execute code that calls tools directly within the code execution environment, eliminating round-trips through the model for each tool invocation. This approach significantly reduces latency and token consumption, especially when dealing with large datasets or sequential tool dependencies. The cookbook demonstrates PTC using a team expense management API scenario where Claude analyzes employee expenses across multiple tool calls, filters irrelevant data programmatically, and identifies budget overages without excessive context window usage.

OpenClaw v2026.3.1 release introduces major enhancements across multiple platforms including adaptive thinking defaults for Claude 4.6, Kubernetes health check endpoints, expanded Android device capabilities (camera, notifications, sensors), Discord/Telegram session management improvements, and WebSocket-first OpenAI streaming. The release also adds localization support (German, zh-CN), Feishu document/chat tooling, LanceDB memory customization, and numerous reliability fixes for Android, Windows, LINE, and Slack integrations.

gpt-code-search is an open-source tool that enables natural language code search across any codebase using OpenAI's GPT-4 and function calling. It runs locally without requiring code indexing or repository uploads, offering functions like search_codebase, get_file_tree, and get_file_contents to help the LLM retrieve and analyze code context.

A custom MCP (Model Context Protocol) server that connects Blender to LLMs like ChatGPT and Claude, enabling natural language control of 3D scene generation. Users can describe complex environments (villages, landscapes, animations) in plain text and the system automatically builds them in Blender with support for spatial reasoning, iterative editing, and object hierarchy management.

Wild Moose is an autonomous AI agent designed for production debugging that connects to observability data like logs and metrics from Datadog. Rather than focusing on code generation, it performs root-cause analysis by exploring multiple data sources through conversational interfaces, combining code execution with API invocations to answer debugging questions.

Nous is an open-source TypeScript agent framework combining features of CrewAI, OpenDevon, and LangFuse, designed for building autonomous and software engineering agents with integrated tooling. It includes a Web UI, database persistence, tracing, human-in-the-loop functionality, and a novel autonomous agent that generates Python code executed in a WebAssembly sandbox for improved reasoning and reduced LLM costs.

BrowserOS is an open-source Chromium fork enabling non-developers to create and run browser agents locally. After testing three UX approaches (drag-and-drop workflows, one-shot agents, and plan-follower agents), the team found that having users provide simple natural language plans while the LLM executes each step achieved the best balance—improving success rates from 30% to ~80% even with local models like those run via Ollama or LMStudio.

The article argues that building custom workplace search products using LLMs is now economically viable and preferable to buying expensive vendor solutions. Modern tools like LangChain, LlamaIndex, and vector databases enable companies to build sophisticated internal search chatbots in days rather than months, with full customization and lower costs than traditional enterprise search products.

Shuttle AI is a tool that generates and deploys fully functional Rust backends from a single natural language prompt using multiple coordinated GPT agents. Users can create complete services like blog platforms or Twitter clones with commands like `shuttle-ai build "Build me a blog service"`, which handles specification generation, code creation, error checking, infrastructure provisioning, and cloud deployment.

Skyfall AI created Mini Amusement Parks (MAPs), a RollerCoaster Tycoon-style business simulator benchmark to evaluate whether AI agents can manage real business operations with stochastic events, incomplete information, and resource constraints. Testing revealed humans outperformed GPT-5 agents by 9.8x, with AI systems failing at long-term planning, maintenance prioritization, and handling randomness—demonstrating that current LLMs lack the operational intelligence needed for true AI CEO capabilities.

Skyvern is an open-source AI agent platform that automates browser-based workflows using LLMs, allowing users to define goal-based prompts to complete complex tasks across websites without brittle code-based solutions. The platform features a React UI for real-time monitoring, workflow chaining, authenticated sessions with 2FA support, and cached workflows for reusable interactions, with token costs reduced 80% using GPT-4O.