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Agent Skill · 研究检索

openclaw-qa-testing(OpenClaw QA 测试)

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

openclaw-qa-testing 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 40,273。

总安装 1,307周安装 55GitHub Stars 366,395下载 458核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:openclaw-qa-testing(OpenClaw QA 测试)
来源仓库:https://github.com/steipete/clawdis
仓库路径:skills/openclaw-qa-testing
安装命令:
npx skills add https://github.com/steipete/clawdis --skill openclaw-qa-testing
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/steipete/clawdis --skill openclaw-qa-testing

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于辅助测试设计、自动化测试和回归验证。适合让 Agent 编写单元测试、端到端测试或根据日志定位问题。支持测试框架集成、用例整理和失败分析。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。使用时需确认运行命令、夹具数据及环境隔离要求。

openclaw-qa-testing 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/openclaw-qa-testing

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/steipete/clawdis --skill openclaw-qa-testing;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

openclaw-qa-testing 怎么安装?

在终端执行 npx skills add https://github.com/steipete/clawdis --skill openclaw-qa-testing。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

openclaw-qa-testing 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

openclaw-qa-testing 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

openclaw-qa-testing 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

openclaw-qa-testing 用的人多吗?

公开数据是累计安装 1,307 次,近一周安装 55 次,下载 458 次,GitHub 366,395 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

openclaw-qa-testing 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 366,395 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
openclaw-qa-testing

OpenClaw QA 测试 · 本页

1,307366,395需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

OpenClaw QA Testing

Use this skill for qa-lab / qa-channel work. Repo-local QA only.

Read first

  • docs/concepts/qa-e2e-automation.md
  • docs/help/testing.md
  • docs/channels/qa-channel.md
  • qa/README.md
  • qa/scenarios/index.md
  • extensions/qa-lab/src/suite.ts
  • extensions/qa-lab/src/character-eval.ts

Model policy

  • Live OpenAI lane: openai/gpt-5.4
  • Fast mode: on
  • Do not use:

- openai/gpt-5.4-pro - openai/gpt-5.4-mini

  • Only change model policy if the user explicitly asks.

Default workflow

  1. Read the scenario pack and current suite implementation.
  2. Decide lane:

- mock/dev: mock-openai - real validation: live-frontier

  1. For live OpenAI, use:
OPENCLAW_LIVE_OPENAI_KEY="${OPENAI_API_KEY}" \
pnpm openclaw qa suite \
  --provider-mode live-frontier \
  --model openai/gpt-5.4 \
  --alt-model openai/gpt-5.4 \
  --output-dir .artifacts/qa-e2e/run-all-live-frontier-<tag>
  1. Watch outputs:

- summary: .artifacts/qa-e2e/run-all-live-frontier-<tag>/qa-suite-summary.json - report: .artifacts/qa-e2e/run-all-live-frontier-<tag>/qa-suite-report.md

  1. If the user wants to watch the live UI, find the current openclaw-qa listen port and report http://127.0.0.1:<port>.
  2. If a scenario fails, fix the product or harness root cause, then rerun the full lane.

OTEL smoke

For local QA-lab OpenTelemetry validation, use:

pnpm qa:otel:smoke

This starts a local OTLP/HTTP trace receiver, runs the otel-trace-smoke scenario through qa-channel, decodes the emitted protobuf spans, and verifies the exported trace names and privacy contract. It does not require Opik, Langfuse, or external collector credentials.

Matrix live profiles

pnpm openclaw qa matrix defaults to the full all profile. Use explicit profiles for faster CI/release proof:

OPENCLAW_QA_MATRIX_NO_REPLY_WINDOW_MS=3000 \
pnpm openclaw qa matrix --profile fast --fail-fast
  • fast: release-critical transport contract, excluding generated image and deep E2EE recovery inventory.
  • transport, media, e2ee-smoke, e2ee-deep, e2ee-cli: sharded full Matrix coverage.
  • QA-Lab - All Lanes uses explicit fast Matrix on scheduled runs. Manual dispatch keeps matrix_profile=all as the default and always shards that full Matrix selection.

QA credentials and 1Password

  • Use op only inside tmux for QA secret lookup in this repo.
  • Quick auth check inside tmux:
op account list
  • Direct Telegram npm live test secrets currently live in 1Password item:

- vault: OpenClaw - item: Telegram E2E

  • That item is the first place to look for:

- OPENCLAW_QA_TELEGRAM_DRIVER_BOT_TOKEN - OPENCLAW_QA_TELEGRAM_SUT_BOT_TOKEN - OPENCLAW_QA_PROVIDER_MODE - OPENCLAW_NPM_TELEGRAM_PACKAGE_SPEC

  • Convex QA secrets currently live in 1Password items:

- vault: OpenClaw - item: OPENCLAW_QA_CONVEX_SITE_URL - item: OPENCLAW_QA_CONVEX_SECRET_MAINTAINER - item: OPENCLAW_QA_CONVEX_SECRET_CI

  • Additional related notes/login items seen during QA credential work:

- vault: Private - items: OPENCLAW QA, Convex, Telegram

  • If a required value is missing from those notes:

- do not guess - ask the maintainer/operator for the current value or the current 1Password item name - for Telegram direct runs, OPENCLAW_QA_TELEGRAM_GROUP_ID may be stored separately from Telegram E2E - for Convex runs, the leased Telegram credential should provide the Telegram group id and bot tokens together; do not require a separate OPENCLAW_QA_TELEGRAM_GROUP_ID - for Convex runs, prefer OpenClaw/OPENCLAW_QA_CONVEX_SITE_URL; if that is stale or unclear, ask for the active pool URL before running

  • Prefer direct Telegram envs for the npm Telegram Docker lane when available:
OPENCLAW_QA_TELEGRAM_GROUP_ID="..." \
OPENCLAW_QA_TELEGRAM_DRIVER_BOT_TOKEN="..." \
OPENCLAW_QA_TELEGRAM_SUT_BOT_TOKEN="..." \
OPENCLAW_QA_PROVIDER_MODE="mock-openai" \
OPENCLAW_NPM_TELEGRAM_PACKAGE_SPEC="openclaw@beta" \
pnpm test:docker:npm-telegram-live
  • Prefer Convex mode when the goal is stable shared QA infra:

- round-robin credential leasing - thinner wrapper for channel-specific setup - CLI/admin flows around the pooled credentials

  • Live npm Telegram Docker lane note:

- scripts/e2e/npm-telegram-live-runner.ts reads OPENCLAW_NPM_TELEGRAM_PROVIDER_MODE - do not assume OPENCLAW_QA_PROVIDER_MODE is consumed by that wrapper - if a 1Password note only gives OPENCLAW_QA_PROVIDER_MODE, map it explicitly to OPENCLAW_NPM_TELEGRAM_PROVIDER_MODE before running the Docker lane

  • Verified live shape:

- Convex mode can pass the real Docker lane without direct Telegram env vars - leased Telegram payload includes the group id coupled to the driver/SUT tokens - a real run of pnpm test:docker:npm-telegram-live passed with: - OPENCLAW_QA_CREDENTIAL_SOURCE=convex - OPENCLAW_QA_CREDENTIAL_ROLE=maintainer - OPENCLAW_QA_CONVEX_SITE_URL - OPENCLAW_QA_CONVEX_SECRET_MAINTAINER - OPENCLAW_NPM_TELEGRAM_PROVIDER_MODE=mock-openai

Character evals

Use qa character-eval for style/persona/vibe checks across multiple live models.

pnpm openclaw qa character-eval \
  --model openai/gpt-5.4,thinking=xhigh \
  --model openai/gpt-5.2,thinking=xhigh \
  --model openai/gpt-5,thinking=xhigh \
  --model anthropic/claude-opus-4-6,thinking=high \
  --model anthropic/claude-sonnet-4-6,thinking=high \
  --model zai/glm-5.1,thinking=high \
  --model moonshot/kimi-k2.5,thinking=high \
  --model google/gemini-3.1-pro-preview,thinking=high \
  --judge-model openai/gpt-5.4,thinking=xhigh,fast \
  --judge-model anthropic/claude-opus-4-6,thinking=high \
  --concurrency 16 \
  --judge-concurrency 16 \
  --output-dir .artifacts/qa-e2e/character-eval-<tag>
  • Runs local QA gateway child processes, not Docker.
  • Preferred model spec syntax is provider/model,thinking=<level>[,fast|,no-fast|,fast=<bool>] for both --model and --judge-model.
  • Do not add new examples with separate --model-thinking; keep that flag as legacy compatibility only.
  • Defaults to candidate models openai/gpt-5.4, openai/gpt-5.2, openai/gpt-5, anthropic/claude-opus-4-6, anthropic/claude-sonnet-4-6, zai/glm-5.1, moonshot/kimi-k2.5, and google/gemini-3.1-pro-preview when no --model is passed.
  • Candidate thinking defaults to high, with xhigh for OpenAI models that support it. Prefer inline --model provider/model,thinking=<level>; --thinking <level> and --model-thinking <provider/model=level> remain compatibility shims.
  • OpenAI candidate refs default to fast mode so priority processing is used where supported. Use inline ,fast, ,no-fast, or ,fast=false for one model; use --fast only to force fast mode for every candidate.
  • Judges default to openai/gpt-5.4,thinking=xhigh,fast and anthropic/claude-opus-4-6,thinking=high.
  • Report includes judge ranking, run stats, durations, and full transcripts; do not include raw judge replies. Duration is benchmark context, not a grading signal.
  • Candidate and judge concurrency default to 16. Use --concurrency <n> and --judge-concurrency <n> to override when local gateways or provider limits need a gentler lane.
  • Scenario source should stay markdown-driven under qa/scenarios/.
  • For isolated character/persona evals, write the persona into SOUL.md and blank IDENTITY.md in the scenario flow. Use SOUL.md + IDENTITY.md only when intentionally testing how the normal OpenClaw identity combines with the character.
  • Keep prompts natural and task-shaped. The candidate model should receive character setup through SOUL.md, then normal user turns such as chat, workspace help, and small file tasks; do not ask "how would you react?" or tell the model it is in an eval.
  • Prefer at least one real task, such as creating or editing a tiny workspace artifact, so the transcript captures character under normal tool use instead of pure roleplay.

Codex CLI model lane

Use model refs shaped like codex-cli/<codex-model> whenever QA should exercise Codex as a model backend.

Examples:

pnpm openclaw qa suite \
  --provider-mode live-frontier \
  --model codex-cli/<codex-model> \
  --alt-model codex-cli/<codex-model> \
  --scenario <scenario-id> \
  --output-dir .artifacts/qa-e2e/codex-<tag>
pnpm openclaw qa manual \
  --model codex-cli/<codex-model> \
  --message "Reply exactly: CODEX_OK"
  • Treat the concrete Codex model name as user/config input; do not hardcode it in source, docs examples, or scenarios.
  • Live QA preserves CODEX_HOME so Codex CLI auth/config works while keeping HOME and OPENCLAW_HOME sandboxed.
  • Mock QA should scrub CODEX_HOME.
  • If Codex returns fallback/auth text every turn, first check CODEX_HOME, ~/.profile, and gateway child logs before changing scenario assertions.
  • For model comparison, include codex-cli/<codex-model> as another candidate in qa character-eval; the report should label it as an opaque model name.

Repo facts

  • Seed scenarios live in qa/.
  • Main live runner: extensions/qa-lab/src/suite.ts
  • QA lab server: extensions/qa-lab/src/lab-server.ts
  • Child gateway harness: extensions/qa-lab/src/gateway-child.ts
  • Synthetic channel: extensions/qa-channel/

What “done” looks like

  • Full suite green for the requested lane.
  • User gets:

- watch URL if applicable - pass/fail counts - artifact paths - concise note on what was fixed

Common failure patterns

  • Live timeout too short:

- widen live waits in extensions/qa-lab/src/suite.ts

  • Discovery cannot find repo files:

- point prompts at repo/... inside seeded workspace

  • Subagent proof too brittle:

- prefer stable final reply evidence over transient child-session listing

  • Harness “rebuild” delay:

- dirty tree can trigger a pre-run build; expect that before ports appear

When adding scenarios

  • Add or update scenario markdown under qa/scenarios/
  • Keep kickoff expectations in qa/scenarios/index.md aligned
  • Add executable coverage in extensions/qa-lab/src/suite.ts
  • Prefer end-to-end assertions over mock-only checks
  • Save outputs under .artifacts/qa-e2e/

平台分布

Codex

33.94%
按下载量换算155

Claude

30.7%
按下载量换算141

Cursor

21.55%
按下载量换算99

Gemini CLI

10.9%
按下载量换算50

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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