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Agent Skill · 研究检索

intelligems-test-verdict(智力测试结论)

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。

intelligems-test-verdict 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,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 71,596。

总安装 194周安装 8GitHub Stars 2下载 63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:intelligems-test-verdict(智力测试结论)
来源仓库:https://github.com/victorpay1/intelligems-analytics
仓库路径:skills/intelligems-test-verdict
安装命令:
npx skills add https://github.com/victorpay1/intelligems-analytics --skill intelligems-test-verdict
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/victorpay1/intelligems-analytics --skill intelligems-test-verdict

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、用例整理和回归验证,适合编写单元测试、端到端测试或根据失败日志定位问题。使用时需确认项目测试框架、运行命令和夹具数据,避免为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。支持生成测试计划和验证逻辑,提升测试覆盖率和稳定性。

建议在提示词中明确确认步骤、权限边界和失败处理方式。

来源仓库内路径:skills/intelligems-test-verdict

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/victorpay1/intelligems-analytics --skill intel…;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

    它需要接触敏感数据,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

intelligems-test-verdict 怎么安装?

在终端执行 npx skills add https://github.com/victorpay1/intelligems-analytics --skill intelligems-tes…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

intelligems-test-verdict 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。

intelligems-test-verdict 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

intelligems-test-verdict 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。

intelligems-test-verdict 用的人多吗?

公开数据是累计安装 194 次,近一周安装 8 次,下载 63 次,GitHub 2 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。

intelligems-test-verdict 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
intelligems-test-verdict

智力测试结论 · 本页

1942接触敏感数据未明确未通过

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

/test-verdict

Analyze any Intelligems A/B test and deliver a clear verdict: WINNER, LOSER, FLAT, KEEP RUNNING, or TOO EARLY. Includes risk framing, revenue-vs-conversion analysis, and a device segment quick-check.

Works with both active and ended tests.


Step 0: Workspace Check

Check if the shared workspace exists and is ready:

test -d ~/intelligems-analytics/venv && test -f ~/intelligems-analytics/ig_client.py && echo "READY" || echo "NEEDS_SETUP"

If NEEDS_SETUP: Run the /intelligems-core skill first to set up the workspace. This installs the shared Python libraries and virtual environment at ~/intelligems-analytics/.

Specifically:

  1. Copy setup_workspace.sh from the intelligems-core skill's references/ folder and run it.
  2. Copy all four core Python files (ig_client.py, ig_metrics.py, ig_helpers.py, ig_config.py) from intelligems-core/references/ into ~/intelligems-analytics/.

Step 1: Get API Key

Check if an API key is already configured:

source ~/intelligems-analytics/venv/bin/activate && python3 -c "
from dotenv import load_dotenv; import os
load_dotenv(os.path.expanduser('~/intelligems-analytics/.env'))
key = os.getenv('INTELLIGEMS_API_KEY', '')
print('HAS_KEY' if key and key != 'your_api_key_here' else 'NO_KEY')
"

If NO_KEY: Ask the user:

"What's your Intelligems API key? You can get one by contacting support@intelligems.io"

Then save it:

echo "INTELLIGEMS_API_KEY=<user's key>" > ~/intelligems-analytics/.env

Never hardcode or assume an API key.


Step 2: Copy Verdict Script

Copy the verdict script from this skill's references into the workspace:

cp references/verdict.py ~/intelligems-analytics/verdict.py

Step 3: Select Test

The script accepts an optional test ID as an argument.

If the user already specified a test ID or name:

  • Pass the ID directly: python3 verdict.py <test_id>

If no test was specified:

  • Run the script without arguments — it will list all active experiments and ask the user to pick one.
  • If the user wants to analyze an ended test, they need to provide the test ID directly.

Step 4: Run Analysis

Execute the verdict script with the workspace virtual environment:

cd ~/intelligems-analytics && source venv/bin/activate && python3 verdict.py [optional_test_id]

The script will:

  1. Fetch overview analytics for the selected test
  2. Run a maturity check (enough time, visitors, orders?)
  3. Compute the verdict based on confidence and uplift
  4. Check revenue vs. conversion alignment
  5. Fetch device-type segments for a quick contradiction check
  6. Print all results in a structured format

Step 5: Present Verdict

Read the script output and present results conversationally. Structure your response like this:

1. Big Verdict Headline

Lead with the verdict in bold. Make it unmistakable:

  • WINNER — "This test is a winner. Roll it out."
  • LOSER — "This test is hurting performance. Kill it."
  • FLAT — "No meaningful difference. Your call."
  • KEEP RUNNING — "Promising signals, but not enough data yet."
  • TOO EARLY — "Way too early to tell. Check back later."

2. Plain-English Reasoning

Explain WHY in one or two sentences. No jargon. Reference the actual numbers.

3. Risk Framing

Always frame confidence as risk:

"At 82% confidence, there's an 18% chance the control was actually better."

If COGS data exists, note whether profit and revenue agree.

4. Revenue vs. Conversion Note

If they diverge, explain what it means in plain English:

"Revenue is up but conversion is down — fewer people are buying, but those who do spend more. That's worth watching."

If aligned, just say: "Revenue and conversion are moving together — clean signal."

5. Segment Quick-Check

Highlight the most interesting finding from the device segment check. Especially flag contradictions:

"Overall this is a winner, but it's actually losing on mobile. Worth investigating before rolling out."

6. What to Test Next

Based on the test type and outcome, suggest what to explore next. Examples:

  • Pricing winner: "Try testing a slightly higher price point to find the ceiling."
  • Shipping loser: "Consider testing free shipping with a minimum order threshold."
  • Content flat: "The messaging isn't moving the needle. Try a completely different angle."
  • Too early: "Just wait. Check back in X days when you'll have enough orders."

Step 6: Set Up Slack Automation (Optional)

If the user wants verdicts delivered to Slack automatically, set up a Slack integration:

1. Get a Slack webhook URL

Ask the user:

"To send verdicts to Slack, you need an Incoming Webhook URL. Go to https://api.slack.com/apps → Create New App → Incoming Webhooks → Add New Webhook. Which channel should verdicts go to?"

2. Copy the Slack module

cp ../intelligems-core/references/ig_slack.py ~/intelligems-analytics/ig_slack.py

3. Test it

Run the verdict with the --slack flag:

cd ~/intelligems-analytics && source venv/bin/activate && python3 verdict.py <test_id> --slack "<webhook_url>"

Verify the message appears in Slack with the verdict emoji, reasoning, risk, and segments.

4. Schedule it (optional)

Copy and run the automation setup script:

cp ../intelligems-core/references/setup_automation.sh ~/intelligems-analytics/
bash ~/intelligems-analytics/setup_automation.sh verdict.py "<webhook_url>" 9 0

This creates a macOS LaunchAgent that runs the verdict daily at 9:00 AM and posts to Slack.


Notes

  • Ended tests: The skill works with ended tests — just pass the test ID directly. The script handles both active and ended tests.
  • Multi-variation tests: If a test has multiple variants, the script analyzes each and highlights the best one.
  • COGS data: When available, the script automatically uses Gross Profit per Visitor (GPV) instead of Revenue per Visitor (RPV) as the primary metric.
  • Slack output: When using --slack, the script formats results as Slack Block Kit messages with verdict emoji, reasoning, risk assessment, and segment insights.

平台分布

Codex

37.3%
按下载量换算23

Claude

28.05%
按下载量换算18

Cursor

17.03%
按下载量换算11

Gemini CLI

8.79%
按下载量换算6

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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