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将 AI Agent 从被动执行转变为主动协作，提供 WAL 协议、工作缓冲区、自主 Cron 等自驱动行为模式。触发：构建 Agent 自主性、自我改进循环、主动行为。不适用于：一次性任务、简单命令执行、非 Agent 工作流。
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Based on SOC occupation classification
| name | proactive-agent |
| version | 3.1.0 |
| description | 将 AI Agent 从被动执行转变为主动协作，提供 WAL 协议、工作缓冲区、自主 Cron 等自驱动行为模式。触发：构建 Agent 自主性、自我改进循环、主动行为。不适用于：一次性任务、简单命令执行、非 Agent 工作流。 |
| author | halthelobster |
By Hal Labs — Part of the Hal Stack
A proactive, self-improving architecture for your AI agent. Most agents just wait — this one anticipates your needs and gets better at it over time.
Proactive — creates value without being asked
Persistent — survives context loss
Self-improving — gets better at serving you
cp assets/*.md ./ONBOARDING.md and offers to get to know you./scripts/security-audit.shworkspace/
├── ONBOARDING.md # First-run setup (tracks progress)
├── AGENTS.md # Operating rules, learned lessons, workflows
├── SOUL.md # Identity, principles, boundaries
├── USER.md # Human's context, goals, preferences
├── MEMORY.md # Curated long-term memory
├── SESSION-STATE.md # ⭐ Active working memory (WAL target)
├── HEARTBEAT.md # Periodic self-improvement checklist
├── TOOLS.md # Tool configurations, gotchas, credentials
└── memory/
├── YYYY-MM-DD.md # Daily raw capture
└── working-buffer.md # ⭐ Danger zone log
| File | Purpose | Update Frequency |
|---|---|---|
SESSION-STATE.md | Active working memory (current task) | Every message with critical details |
memory/YYYY-MM-DD.md | Daily raw logs | During session |
MEMORY.md | Curated long-term wisdom | Periodically distill from daily logs |
The Rule: If it's important enough to remember, write it down NOW — not later.
| Topic | Reference |
|---|---|
| WAL Protocol, Working Buffer, Compaction Recovery, Unified Search | wal-and-memory.md |
| Security Hardening, Relentless Resourcefulness, ADL/VFM Guardrails | security-and-guardrails.md |
| Autonomous vs Prompted Crons, Verify Implementation, Tool Migration | operational-patterns.md |
| Six Pillars, Heartbeat, Reverse Prompting, Growth Loops | pillars-and-growth.md |
The mindset shift: Don't ask "what should I do?" Ask "what would genuinely delight my human that they haven't thought to ask for?"
| Skill | Purpose |
|---|---|
| Proactive Agent (this) | Act without being asked, survive context loss |
| Bulletproof Memory | Detailed SESSION-STATE.md patterns |
| PARA Second Brain | Organize and find knowledge |
| Agent Orchestration | Spawn and manage sub-agents |
License: MIT — use freely, modify, distribute. No warranty. Created by: Hal 9001 (@halthelobster)
Part of the Hal Stack 🦞 "Every day, ask: How can I surprise my human with something amazing?"
Fast headless browser automation for AI agents (Rust-based with Node.js fallback). Navigate, click, type, and snapshot pages via structured commands. Triggers on browser automation, headless browsing, page snapshot. NOT for: websites needing login/cookies (use bb-browser or browser profile), or simple URL content extraction (use web_fetch/firecrawl).
Search, download, and summarize academic papers from arXiv. Built for AI/ML researchers.
将网站操作封装为 CLI 命令，覆盖 Twitter、Reddit、GitHub、知乎、B站、微博等 36 个平台 103 条命令。直接使用 OpenClaw 浏览器，无需额外扩展。触发：需要程序化操作特定平台。适用于需要与特定平台交互的场景。不适用于通用网页抓取（用 firecrawl）、无平台上下文的浏览器自动化、本地文件操作。
自动化浏览器交互：网页测试、表单填写、截图、数据提取。触发：需要导航网站、与网页交互、填写表单、截图、提取信息。需要浏览器工具可用。不适用于简单 URL 抓取（用 web_fetch）、需要完整渲染的 JS 重度站点（用 firecrawl）、批量无头自动化（用 agent-browser）。
"通过 HTTP API 控制浏览器自动化：页面导航、元素交互（点击/输入/选择）、数据提取、无障碍快照、截图、JS 执行、批量操作。触发：需要通过 API 程序化控制浏览器。不适用于：一次性简单浏览器任务（用 agent-browser）、平台特定交互（用 bb-browser）。"
适配国内 Git 平台和团队习惯的工作流规范——Gitee、Coding、极狐 GitLab、CNB 全覆盖