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agent-qa-gatesAgent 质量保证门

Agent Skill

agent-qa-gates 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

9,720

周安装

401

GitHub Stars

公开资料未说明

下载量

3,176
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:agent-qa-gates(Agent 质量保证门)
来源仓库:https://github.com/zurbrick/agent-qa-gates
安装命令:
openclaw skills install agent-qa-gates
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install agent-qa-gates

简介

作为 AI 代理输出的验证门,防止幻觉数据、上下文泄露与格式错误。

  • 适用于关键决策、对外接口与用户交互质量保障场景。
  • 可拦截重复发送、压缩漂移与越权信息返回。
  • 使用前应定义清晰的验证规则与 fallback 策略。
  • 建议结合人工审核通道处理边缘案例。agent-qa-gates 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
agent-qa-gates
version
1.2.0
description
Output validation gates for AI agent systems. Prevents hallucinated data, leaked internal context, wrong formats, duplicate sends, post-compaction drift, and false delegated completions. Use when building or operating an agent that delivers output to humans or external systems. Provides a tiered gate system (internal → user-facing → external → code), protocol gates for recurring failure modes, delegated-work acceptance gates, severity classification, and a feedback loop for gate evolution. Triggers on phrases like "QA gates", "validation", "output quality", "prevent hallucination", "delivery checklist", "agent QA".

Agent QA Gates

A field-tested validation system for AI agent output. Born from production failures, not theory.

Quick Start

Before any agent delivers output, run the Pre-Ship Checklist:

  1. Accurate? — every number/date/metric has a source. Unsourced → prefix "estimated"
  2. Complete? — no missing pieces, no "I'll do that next"
  3. Actionable? — ends with clear next step or decision point
  4. Fits the channel? — check character limits for your delivery surface
  5. No leaks? — no internal context, private data, or secrets
  6. Not a duplicate? — verify no recent identical send
  7. Would the human be embarrassed? — if yes, don't ship

Gate Tiers

Four ascending tiers by risk level:

GateScopeKey Checks
Gate 0Internal (files, config, memory)Mechanism changed not just text, no placeholders, file exists
Gate 1Human-facing (briefings, summaries)Key info in first 2 lines, ≤3-line paragraphs, channel length limits
Gate 2External (email, public content, client materials)No internal context leaked, recipient-appropriate tone, dedup check
Gate 3Code & technicalBuilds clean, no secrets in code, error handling, tests pass

See references/gates-detail.md for full gate checklists.

Severity Classification

Not all failures are equal:

  • 🔴 BLOCK — cannot ship (secrets, privacy, hallucinated data, wrong recipient)
  • 🟡 FIX — fix before shipping, <2 min (formatting, too long, missing citation)
  • 🟢 NOTE — log and ship (style preference, minor optimization)

Protocol Gates

Recurring failure modes need dedicated gates. These are the most common:

Heartbeat / Periodic Check Output

  • Binary output: alert text ONLY or status-OK ONLY. Never mixed.
  • Every data point verified by current-session tool call. No hallucinated metrics.
  • No stale data from previous cycles or pre-compaction sessions.

Post-Compaction / Context Reset

  • Do not trust facts from the pre-reset session — verify from files and tools.
  • Rerun pending checks from scratch.
  • Zero carryover for periodic checks.

Scheduled Job / Cron Changes

  • Explicit timeout set
  • Explicit model set
  • Verify schedule after creation
  • Output fits destination channel limits

Sub-Agent Output Review

  • Does output match the brief's success criteria?
  • Any uncertainty flags unresolved?
  • Is the reasoning (not just the conclusion) sound?

Isolated Agent / Cron Output (real-world data)

For any cron or sub-agent that reports external data without orchestrator review:

  • Did the agent make a verifiable live tool call? Is the raw response traceable?
  • Any names, dates, amounts, or IDs that can't be traced to a tool result? → 🔴 BLOCK
  • If tool call failed: output must be DATA_UNAVAILABLE — [reason], not fabricated data
  • Does the cron prompt include the Real-World Data Verification Rule?

Severity: Fabricated real-world data = 🔴 BLOCK. Same as hallucinated metrics.

Delegated Work Acceptance

For any non-trivial delegated task (especially builds, audits, config changes, or external deliverables):

  • Does the handoff include a clear artifact path or proof object?
  • Did the worker report exact commands run rather than vague claims?
  • Did verification actually happen, with results stated?
  • Is the output non-empty and specific, not just "done" or "completed successfully"?
  • Are known gaps / next actions named explicitly?
  • If the handoff is empty, artifact-free, or self-certifying without proof → 🔴 BLOCK
  • Valid dispositions: Done, Revision Needed, Blocked, Failed, Stale

Silent Worker / Stale Task Classification

For delegated work that appears to be running:

  • Was the spawn actually accepted? If not, it is not running.
  • No start signal within 10 minutes after accepted spawn → Stale
  • No materially new output for 30 minutes on active work → Stale unless the task explicitly justifies a longer quiet window
  • Stale work must be investigated, respawned, or escalated — never left as indefinite In Progress

Gate Evolution

Gates should evolve based on real failures, not imagination:

  1. When a failure occurs → log it with root cause
  2. Same failure class occurs 2+ times → add a gate item
  3. Monthly: prune gates that haven't caught anything in 60 days

Anti-Patterns

  • Gates that sound good but never catch anything → kill them
  • Per-agent checklists that duplicate general gates → merge or reference
  • "ADHD-friendly" or "high-quality" as gate items → not testable, replace with mechanical checks
  • Aspirational gates nobody runs → either automate or cut

Adapting to Your System

This skill provides the pattern. Adapt it:

  1. Start with the Pre-Ship Checklist — it works for any agent system
  2. Add Protocol Gates for your top 3 recurring failure modes
  3. Set channel limits for your delivery surfaces
  4. Map real failures to gates — if a failure isn't gated, add the gate
  5. Kill gates that never fire — a shorter, sharper checklist wins

For the full reference implementation, see references/gates-detail.md. For automation scripts, see scripts/qa-check.sh.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

79.81%
按下载量换算2,535

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install agent-qa-gates 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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