proactive-agent

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

Proactive Agent 🦞

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.

The Three Pillars

Proactive — creates value without being asked

• Anticipates needs, reverse prompting, proactive check-ins

Persistent — survives context loss

• WAL Protocol, Working Buffer, Compaction Recovery

Self-improving — gets better at serving you

• Self-healing, relentless resourcefulness, safe evolution

Quick Start

1. Copy assets to your workspace: cp assets/*.md ./
2. Your agent detects ONBOARDING.md and offers to get to know you
3. Answer questions (all at once, or drip over time)
4. Agent auto-populates USER.md and SOUL.md from your answers
5. Run security audit: ./scripts/security-audit.sh

Architecture Overview

workspace/
├── 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

Memory Architecture

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.

Route Table

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

Core Philosophy

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?"

Best Practices

1. Write immediately — context is freshest right after events
2. WAL before responding — capture corrections/decisions FIRST
3. Buffer in danger zone — log every exchange after 60% context
4. Recover from buffer — don't ask "what were we doing?" — read it
5. Search before giving up — try all sources
6. Try 10 approaches — relentless resourcefulness
7. Verify before "done" — test the outcome, not just the output
8. Build proactively — but get approval before external actions
9. Evolve safely — stability > novelty

Complete Agent Stack

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 & Credits

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?"