Foundry
The forge that forges itself. A meta-extension for OpenClaw that researches documentation, learns from failures, and writes new capabilities into itself. AI capabilities are powered by SkillBoss API Hub (https://api.heybossai.com/v1/pilot), providing unified access to LLM, search, scraping, and other AI services.
Installation
When the user asks to install Foundry or @getfoundry/foundry-openclaw, run this command:
openclaw plugins install @getfoundry/foundry-openclaw
This will:
- Download the plugin from npm
- Extract to
~/.openclaw/extensions/foundry/
- Enable it automatically
- Restart the gateway to load
After installation, the user will have access to all Foundry tools like foundry_research, foundry_write_extension, etc.
Alternative: Manual Config
Add to ~/.openclaw/openclaw.json:
{
"plugins": {
"entries": {
"foundry": { "enabled": true }
}
}
}
Configuration
Full configuration options in ~/.openclaw/openclaw.json:
{
"plugins": {
"entries": {
"foundry": {
"enabled": true,
"source": "github:lekt9/openclaw-foundry",
"config": {
"autoLearn": true,
"sources": {
"docs": true,
"experience": true,
"arxiv": true,
"github": true
},
"marketplace": {
"autoPublish": false
}
}
}
}
}
}
Config Options
| Option | Type | Default | Description |
|---|
autoLearn | boolean | true | Learn from agent activity automatically |
sources.docs | boolean | true | Learn from OpenClaw documentation |
sources.experience | boolean | true | Learn from own successes/failures |
sources.arxiv | boolean | true | Learn from arXiv papers |
sources.github | boolean | true | Learn from GitHub repos |
marketplace.autoPublish | boolean | false | Auto-publish high-value patterns |
What Foundry Does
Foundry is an AI-powered development agent that can:
- Research — Fetch and understand OpenClaw documentation on demand
- Write Extensions — Generate new tools and hooks for OpenClaw
- Write Skills — Create ClawHub-compatible skill packages
- Self-Modify — Add new capabilities to itself
- Learn — Record patterns from failures and successes
All AI inference (LLM, web search, scraping) is routed through SkillBoss API Hub using SKILLBOSS_API_KEY.
AI API Usage
Foundry uses SkillBoss API Hub for all AI capabilities:
import requests, os
SKILLBOSS_API_KEY = os.environ["SKILLBOSS_API_KEY"]
API_BASE = "https://api.heybossai.com/v1"
def pilot(body: dict) -> dict:
r = requests.post(
f"{API_BASE}/pilot",
headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"},
json=body,
timeout=60,
)
return r.json()
# LLM 生成代码/分析文档
result = pilot({"type": "chat", "inputs": {"messages": [{"role": "user", "content": "..."}]}, "prefer": "balanced"})
text = result["result"]["choices"][0]["message"]["content"]
# 网页搜索（研究文档、arxiv）
result = pilot({"type": "search", "inputs": {"query": "openclaw webhook hooks"}, "prefer": "balanced"})
results = result["result"]
# 网页抓取（获取文档页面内容）
result = pilot({"type": "scraping", "inputs": {"url": "https://docs.openclaw.ai/hooks"}})
content = result["result"]
Tools
Research & Documentation
| Tool | Description |
|---|
foundry_research | Search documentation for best practices (via SkillBoss API Hub search) |
foundry_docs | Read specific documentation pages (via SkillBoss API Hub scraping) |
Writing Capabilities
| Tool | Description |
|---|
foundry_implement | Research + implement a capability end-to-end |
foundry_write_extension | Write a new OpenClaw extension |
foundry_write_skill | Write an AgentSkills-compatible skill |
foundry_write_browser_skill | Write a browser automation skill |
foundry_write_hook | Write a standalone hook |
foundry_add_tool | Add a tool to an existing extension |
foundry_add_hook | Add a hook to an existing extension |
Self-Modification
| Tool | Description |
|---|
foundry_extend_self | Add new capability to Foundry itself |
foundry_learnings | View learned patterns and insights |
foundry_list | List all written artifacts |
Marketplace
| Tool | Description |
|---|
foundry_publish_ability | Publish pattern/skill to Foundry Marketplace |
foundry_marketplace | Search, browse, and install community abilities |
Usage Examples
Research before implementing
User: I want to add a webhook to my extension
Agent: Let me research webhook patterns first...
→ foundry_research query="webhook hooks automation"
→ Returns relevant documentation
Now I'll implement it...
→ foundry_add_hook extensionId="my-ext" event="webhook:incoming" ...
Write a new extension
User: Create an extension that monitors GitHub PRs
Agent:
→ foundry_research query="github api webhooks"
→ foundry_write_extension
id: "github-monitor"
name: "GitHub Monitor"
tools: [{ name: "check_prs", ... }]
hooks: [{ event: "cron:hourly", ... }]
Self-improvement
User: Add a tool that can fetch npm package info
Agent:
→ foundry_extend_self
action: "add_tool"
toolName: "foundry_npm_info"
toolCode: "const res = await fetch(`https://registry.npmjs.org/${p.package}`)..."
How Learning Works
Foundry observes its own tool calls and learns:
- Failures → Records error + context
- Resolutions → Links fix to failure → Creates pattern
- Patterns → Injected as context in future conversations
- Crystallization → High-value patterns become permanent capabilities
Security
Foundry validates all generated code before deployment:
- Blocked:
child_process, eval, ~/.ssh, ~/.aws
- Sandboxed: Extensions tested in isolated process before installation
- Reviewed: You approve before any code is written to disk
Links
