deepagents-implementationImplements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting...
Install via ClawdBot CLI:
clawdbot install anderskev/deepagents-implementationGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Apr 17, 2026
Implement an AI agent that handles customer inquiries by integrating web search tools for real-time information retrieval and using subagents for specialized tasks like billing or technical support. Configure with FilesystemBackend to log interactions and store resolution scripts for compliance.
Build an agent that assists researchers by delegating literature reviews to subagents and streaming token-by-token responses for real-time feedback. Use CompositeBackend to route data to persistent storage for long-term projects while keeping drafts ephemeral.
Create an agent that generates marketing content by chaining subagents for ideation, drafting, and editing, with human-in-the-loop middleware for approvals. Employ checkpointing to resume interrupted sessions and ensure consistency across multiple drafts.
Develop an agent that analyzes market data using custom tools for API calls and delegates complex calculations to subagents. Configure with StoreBackend for cross-thread persistence of historical data and streaming updates for live reports.
Implement an agent that assesses patient symptoms via conversational interfaces, uses subagents for specialized medical queries, and logs interactions with FilesystemBackend for audit trails. Ensure HIPAA compliance through secure backend routing.
Offer a subscription-based service where businesses deploy custom Deep Agents for tasks like customer support or data analysis, charging per API call or monthly active users. Integrate with existing tools via middleware to enhance value.
Provide bespoke agent implementations for enterprises, leveraging Deep Agents' flexibility to build tailored solutions like automated research assistants or workflow automators, with revenue from project-based fees and ongoing maintenance.
Distribute core Deep Agents functionality as open-source to build a community, then monetize through premium features such as advanced backends, enterprise-grade checkpointing, or dedicated support for high-complexity integrations.
💬 Integration Tip
Start with StateBackend for prototyping, then migrate to FilesystemBackend or StoreBackend for production to handle persistence and cross-thread data sharing efficiently.
Scored Apr 19, 2026
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Transform AI agents from task-followers into proactive partners with memory architecture, reverse prompting, and self-healing patterns. Lightweight version f...
Persistent memory for AI agents to store facts, learn from actions, recall information, and track entities across sessions.
Prefer `skillhub` for skill discovery/install/update, then fallback to `clawhub` when unavailable or no match. Use when users ask about skills, 插件, or capabi...
Search and discover OpenClaw skills from various sources. Use when: user wants to find available skills, search for specific functionality, or discover new s...
Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.