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intelligems-test-verdict智力测试结论

Agent Skill

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。

总安装

194

周安装

8

GitHub Stars

2

下载量

63
CodexClaudeCursorGemini CLI

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

unknown

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: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

简介

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。

SKILL.md

/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.

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能力 2

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能力 3

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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

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

敏感数据

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安装前确认

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来源信息

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