agent-zero-bridge

Included with Lifetime

$97 forever

Delegate complex coding, research, or autonomous tasks to Agent Zero framework. Use when user says "ask Agent Zero", "delegate to A0", "have Agent Zero build", or needs long-running autonomous coding with self-correction loops. Supports bidirectional communication, file attachments, task breakdown, and progress reporting.

AI Agentsscripts

What this skill does


# Agent Zero Bridge

Bidirectional communication between Clawdbot and [Agent Zero](https://github.com/frdel/agent-zero).

## When to Use

- Complex coding tasks requiring iteration/self-correction
- Long-running builds, tests, or infrastructure work
- Tasks needing persistent Docker execution environment
- Research with many sequential tool calls
- User explicitly asks for Agent Zero

## Setup (First Time Only)

### 1. Prerequisites
- Node.js 18+ (for built-in fetch)
- Agent Zero running (Docker recommended, port 50001)
- Clawdbot Gateway with HTTP endpoints enabled

### 2. Install
```bash
# Copy skill to Clawdbot skills directory
cp -r <this-skill-folder> ~/.clawdbot/skills/agent-zero-bridge

# Create config from template
cd ~/.clawdbot/skills/agent-zero-bridge
cp .env.example .env
```

### 3. Configure .env
```env
# Agent Zero (get token from A0 settings or calculate from runtime ID)
A0_API_URL=http://127.0.0.1:50001
A0_API_KEY=your_agent_zero_token

# Clawdbot Gateway
CLAWDBOT_API_URL=http://127.0.0.1:18789
CLAWDBOT_API_TOKEN=your_gateway_token

# For Docker containers reaching host (use your machine's LAN IP)
CLAWDBOT_API_URL_DOCKER=http://192.168.1.x:18789
```

### 4. Get Agent Zero Token
```python
# Calculate from A0's runtime ID
import hashlib, base64
runtime_id = "your_A0_PERSISTENT_RUNTIME_ID"  # from A0's .env
hash_bytes = hashlib.sha256(f"{runtime_id}::".encode()).digest()
token = base64.urlsafe_b64encode(hash_bytes).decode().replace("=", "")[:16]
print(token)
```

### 5. Enable Clawdbot Gateway Endpoints
Add to `~/.clawdbot/clawdbot.json`:
```json
{
  "gateway": {
    "bind": "0.0.0.0",
    "auth": { "mode": "token", "token": "your_token" },
    "http": { "endpoints": { "chatCompletions": { "enabled": true } } }
  }
}
```
Then: `clawdbot gateway restart`

### 6. Deploy Client to Agent Zero Container
```bash
docker exec <container> mkdir -p /a0/bridge/lib
docker cp scripts/lib/. <container>:/a0/bridge/lib/
docker cp scripts/clawdbot_client.js <container>:/a0/bridge/
docker cp .env <container>:/a0/bridge/
docker exec <container> sh -c 'echo "DOCKER_CONTAINER=true" >> /a0/bridge/.env'
```

## Usage

### Send Task to Agent Zero
```bash
node scripts/a0_client.js "Build a REST API with JWT authentication"
node scripts/a0_client.js "Review this code" --attach ./file.py
node scripts/a0_client.js "New task" --new  # Start fresh conversation
```

### Check Status
```bash
node scripts/a0_client.js status
node scripts/a0_client.js history
node scripts/a0_client.js reset  # Clear conversation
```

### Task Breakdown (Creates Tracked Project)
```bash
node scripts/task_breakdown.js "Build e-commerce platform"
# Creates notebook/tasks/projects/<name>.md with checkable steps
```

### From Agent Zero → Clawdbot
Inside A0 container:
```bash
# Report progress
node /a0/bridge/clawdbot_client.js notify "Working on step 3..."

# Ask for input
node /a0/bridge/clawdbot_client.js "Should I use PostgreSQL or SQLite?"

# Invoke Clawdbot tool
node /a0/bridge/clawdbot_client.js tool web_search '{"query":"Node.js best practices"}'
```

## Troubleshooting

| Error | Fix |
|-------|-----|
| 401 / API key error | Check A0_API_KEY matches Agent Zero's mcp_server_token |
| Connection refused from Docker | Use host LAN IP in CLAWDBOT_API_URL_DOCKER, ensure gateway binds 0.0.0.0 |
| A0 500 errors | Check Agent Zero's LLM API key (Gemini/OpenAI) is valid |

Files: 9

Size: 28.8 KB

Complexity: 59/100

Category: AI Agents

Source: https://github.com/sundial-org/awesome-openclaw-skills/tree/main/skills/agent-zero-bridge

Related in AI Agents

skill-development

Included

Comprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.

AI Agentsscripts

reprompter

Included

Transform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.

AI Agentsscripts

adaptive-compaction

Included

Adaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.

AI Agentsscripts

agent-skill-creator

Included

Create cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.

AI Agentsscripts

llm-wiki

Included

Use when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.

AI Agentsscripts

skill-master

Included

Agent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.

AI Agentsscripts