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Battle-Tested Agent

提供 19 项经生产验证的 Agent 可靠性模式,覆盖记忆、反幻觉、歧义处理、上下文压缩存活、委派与交接、验收门与自省;附带可合并的配置模板、学习/错误记录模板和 bash 工作区审计脚本,按 starter、intermediate、advanced 三层渐进落地,用于加固长期或自主运行的 Agent。

zurbrick
zurbrick
热度 76.52
最近更新 2026-05-11 17:28:01
分类:开发依赖:代码执行 / 读写文件应用场景:工作流 / 模板 / 自动化脚本 / 任务管理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add battle-tested-agent
Metadata
name
battle-tested-agent
version
1.5.0
description
19 production-hardened patterns for AI agents — memory, verification, ambiguity handling, compaction survival, delegation, proof-based handoffs, stale-worker recovery, and self-improvement. Use when hardening an agent for production reliability, when an agent keeps hallucinating or losing context, when handoffs between agents drop details, when delegated work silently fails, or when someone says "my agent is unreliable" or "how do I make this more robust." Works with OpenClaw, Claude Code, Cowork, or any SKILL.md-based agent setup. Includes the Isolated Agent Fabrication Guard plus new delegation hardening patterns for brief quality, completion contracts, acceptance gates, silent-worker recovery, and scoped verifier use.
author
Zye ⚡ (Don Zurbrick)
license
MIT
tags
["production","reliability","memory","compaction","multi-agent","security","self-improvement","heartbeat","delegation","battle-tested"]
homepage
https://github.com/zurbrick/battle-tested-agent
metadata
{"openclaw":{"emoji":"⚔️","requires":{"bins":["bash","grep","find","wc"],"optionalBins":["openclaw"]}}}

Battle-Tested Agent

19 production-hardened patterns for AI agents. Every one earned from failure.

Use this skill when you are:

  • hardening an agent that will run repeatedly or autonomously
  • tightening memory, verification, or anti-hallucination behavior
  • reducing compaction failures, weak handoffs, or orchestration drift
  • reviewing an agent workspace for missing production patterns
  • debugging why an agent keeps losing context, guessing, or dropping work

Do not use this skill for:

  • persona writing or onboarding polish
  • one-off prompt tweaks with no reusable pattern behind them
  • adding new tools, servers, or runtime capabilities
  • turning a simple workspace into process theater

Default workflow

  1. Audit first Run bash scripts/audit.sh <workspace> to see which patterns are present. The script checks for all 16 patterns and tells you what to fix first.

  2. Start with the smallest tier that fits Implement starter patterns first, then intermediate, then advanced. Do not cargo-cult every pattern into every agent.

  3. Patch the actual failure mode Change the mechanism, not just the wording. "ALWAYS check X" is not a fix — a verification gate is a fix.

  4. Keep patterns lightweight Add only the pieces that materially reduce failures or operator burden.

Pattern tiers

  • Starter (5): baseline reliability for almost every agent
  • Intermediate (5): daily-driver patterns for briefs, heartbeats, and recurring work
  • Advanced (6): multi-agent orchestration, handoffs, and self-improvement discipline

Pattern clusters

Some patterns reinforce each other naturally. Adopt them together when the failure mode calls for it:

  • Trust chain: WAL Protocol + Anti-Hallucination + Agent Verification — ensures data is captured, sourced, and measured before reporting
  • Handoff loop: Delegation Rules + Completion Contract + Acceptance Gate + Task State Tracking — prevents work from disappearing between agents or being certified without proof
  • Survival kit: Working Buffer + Compaction Injection Hardening + Silent Worker Recovery — keeps context alive across long sessions and prevents silent delegated drift
  • Quality gate: QA Gates + Verify Implementation + Decision Logs — ensures output quality and traceable reasoning
  • Delegation hardening: Brief Quality Gate + Scoped Verifier Gate — keeps delegation tight without turning the whole system into bureaucracy

When patterns conflict

If two patterns seem to give contradictory advice:

  • Safety patterns win over speed patterns. Ambiguity Gate overrides Simple Path First when the request is ambiguous. Verify before acting, even if the simple path is obvious.
  • Evidence patterns win over action patterns. Anti-Hallucination overrides "just try it" when reporting data. Never guess a number to move faster.

Assets — how to use them

The assets/ folder contains starter files you copy into your workspace and customize. They are templates, not drop-in replacements.

# Merge delegation and decision log rules into your existing AGENTS.md
cp assets/AGENTS-additions.md ~/workspace/ # Review, then merge

# Add QA gates
cp assets/QA-gates.md ~/workspace/QA.md

# Set up self-improvement tracking
mkdir -p ~/workspace/.learnings
cp assets/learnings-template.md ~/workspace/.learnings/LEARNINGS.md
cp assets/errors-template.md ~/workspace/.learnings/ERRORS.md
cp assets/features-template.md ~/workspace/.learnings/FEATURE_REQUESTS.md

Read references/audit-usage.md for the full rollout order and bootstrap workflow.

References

  • references/starter-patterns.md — WAL, anti-hallucination, ambiguity, simple-path-first, unblock-before-shelve
  • references/intermediate-patterns.md — verification, working buffer, QA gates, decision logs, verify implementation
  • references/advanced-patterns.md — delegation, brief quality, proof-based handoffs, acceptance gates, orchestration, stale-worker recovery, compaction hardening, recurrence tracking
  • references/audit-usage.md — audit script usage, install/copy snippets, and expected outcomes

Included scripts

  • scripts/audit.sh — workspace audit for all 19 patterns (supports AGENTS.md, CLAUDE.md, SOUL.md, and system.md)

Rules of thumb

  • Audit before expanding
  • Prefer progressive disclosure over giant core files
  • Silence is better than hallucination
  • Ambiguity is a stop sign, not permission
  • The orchestrator should preserve oversight, not sink into implementation
  • Mechanism changes beat wording changes
  • After acting, verify the new state before declaring success
  • Partial progress is not success; recovery steps matter as much as first-attempt steps

Outcome

A leaner, more resilient agent that survives compaction, hands work off cleanly, reports only what is verified, and improves without spiraling into bureaucracy.