Agent skill

Cohort Analysis

by killvxk in killvxk/pm-skills-zh

对用户参与度数据执行同期群分析——留存曲线、功能采用趋势及分层洞察。适用于按同期群分析用户留存、研究功能随时间的采用情况、调查流失规律,或识别参与度趋势。

MITAuto-check passedData & Analytics

Install Cohort Analysis

skills CLI
$ npx skills add killvxk/pm-skills-zh --skill cohort-analysis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install killvxk/pm-skills-zh cohort-analysis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/killvxk/pm-skills-zh.git skills-src && mkdir -p .claude/skills && cp -r skills-src/pm-data-analytics/skills/cohort-analysis .claude/skills/cohort-analysis && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
cohort-analysis
GitHub stars
168
Token cost
~562 tokens
SKILL.md length
129 words
Files
1
Skills in repo
11
Repo updated
First seen
Licence
MIT

At a glance

对用户参与度数据执行同期群分析——留存曲线、功能采用趋势及分层洞察。适用于按同期群分析用户留存、研究功能随时间的采用情况、调查流失规律,或识别参与度趋势。

  • Works in 6 steps: 包含时间维度:提供跨多个时间周期的数据 → 明确定义同期群:清楚说明同期群的划分依据(注册月份、功能上线日期等) → 提供背景信息:说明该时期内的产品变更、上线内容或重要事件 → …
  • Tasks that involve Product analytics
  • SKILL.md covers 用途, 工作原理, 使用示例 and 核心能力, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Cohort Analysis is an agent skill from killvxk/pm-skills-zh. 对用户参与度数据执行同期群分析——留存曲线、功能采用趋势及分层洞察。适用于按同期群分析用户留存、研究功能随时间的采用情况、调查流失规律,或识别参与度趋势。

Its SKILL.md is about 560 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Data & Analytics, covering Product analytics. It works with Python. The repository describes itself as: PM Skills Marketplace 简体中文版 - 65个产品经理技能和36个工作流,翻译自 https://github.com/phuryn/pm-skills/. The licence is MIT.

When your agent uses it

  • Tasks that involve Product analytics

Example prompts

  • “/cohort-analysis”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. 包含时间维度:提供跨多个时间周期的数据
  2. 明确定义同期群:清楚说明同期群的划分依据(注册月份、功能上线日期等)
  3. 提供背景信息:说明该时期内的产品变更、上线内容或重要事件
  4. 多维指标:包括留存率、参与度、功能使用情况、营收等
  5. 充足数据量:至少 3—4 个同期群,才能发现有意义的规律
  6. 明确输出要求:注明需要可视化图表、Python 脚本还是研究建议

What it can do on your machine

Read from SKILL.md and the folder at commit 5179784. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • productcompass.pm

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cohort Analysis loads about 562 tokens when it runs. Until then it costs about 23 tokens; SKILL.md has 129 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~23
When it runs · the whole SKILL.md, loaded when a task matches
~562

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from killvxk/pm-skills-zh at commit 5179784, republished under its MIT licence (© killvxk). 129 words, ~562 tokens.

Download SKILL.mdSave it as .claude/skills/cohort-analysis/SKILL.md (or your agent's skills folder).
name
cohort-analysis
description
对用户参与度数据执行同期群分析——留存曲线、功能采用趋势及分层洞察。适用于按同期群分析用户留存、研究功能随时间的采用情况、调查流失规律,或识别参与度趋势。

同期群分析与留存探查

用途

通过同期群分析用户参与度和留存规律,识别用户行为、功能采用及长期参与度的趋势。将定量洞察与定性研究建议相结合。

工作原理

第一步:读取并验证数据
  • 接受包含用户同期群信息的 CSV、Excel 或 JSON 数据文件
  • 验证数据结构:同期群标识符、时间周期、参与度指标
  • 检查缺失值和数据质量问题
  • 汇总关键统计信息(同期群规模、日期范围、可用指标)
第二步:生成定量分析
  • 计算同期群留存率和参与度趋势
  • 识别留存曲线、流失节点和异常值
  • 计算各同期群的功能采用率
  • 计算环比或周期性变化
  • 如有需要,使用 pandas 和 numpy 生成 Python 分析脚本
第三步:创建可视化图表
  • 生成留存热力图(同期群 vs. 时间周期)
  • 创建展示同期群走势的折线图
  • 构建功能采用率对比图
  • 可视化流失节点和参与度趋势
  • 输出为交互式图表或静态图片
第四步:识别洞察与规律
  • 发现一个或多个显著规律:
    • 特定同期群的早期高流失
    • 后期参与度变化
    • 功能采用的聚类特征
    • 季节性或时间性趋势
  • 突出意外发现和偏差
  • 与基准线进行同期群绩效对比
第五步:建议后续研究方向
  • 推荐定性研究方法:
    • 与流失用户进行针对性访谈
    • 对高活跃同期群开展功能使用调研
    • 回放关键交互模式的会话录屏
    • 对高留存 vs. 低留存同期群进行赢/输分析
  • 设计后续定量研究
  • 建议 A/B 测试或功能实验

使用示例

示例一:上传 CSV 数据

上传 cohort_engagement.csv,包含以下字段:cohort_month、weeks_active、
user_id、feature_x_usage、engagement_score

需求:"分析留存规律,并找出 Q4 2025 同期群为何相比 Q3 表现欠佳"

示例二:描述数据格式

"我有 2025 年 1—12 月的月度用户同期群。每行包含:
同期群日期、用户 ID、购买频次和客服工单数量。
分析哪些同期群的长期留存率最高。"

示例三:功能采用分析

上传包含同期群采用数据的 feature_usage.xlsx。

需求:"对比各同期群新功能的采用曲线。
哪些同期群采用速度最快?有什么规律?"

核心能力

  • 数据读取:导入 CSV、Excel、JSON、SQL 查询结果
  • 留存分析:计算并可视化随时间变化的留存率
  • 同期群对比:跨同期群对比各项指标
  • 异常检测:标记异常规律或流失节点
  • Python 脚本:生成可复用的分析代码,支持持续分析
  • 可视化:创建热力图、图表和交互式数据看板
  • 研究设计:建议针对性的后续研究和访谈方案
  • 统计摘要:提供定量指标和相关性分析

最佳实践建议

  1. 包含时间维度:提供跨多个时间周期的数据
  2. 明确定义同期群:清楚说明同期群的划分依据(注册月份、功能上线日期等)
  3. 提供背景信息:说明该时期内的产品变更、上线内容或重要事件
  4. 多维指标:包括留存率、参与度、功能使用情况、营收等
  5. 充足数据量:至少 3—4 个同期群,才能发现有意义的规律
  6. 明确输出要求:注明需要可视化图表、Python 脚本还是研究建议

输出格式

你将收到:

  • 数据摘要:同期群概览和数据质量评估
  • 定量发现:关键指标、留存率及趋势分析
  • 可视化图表:展示留存曲线和采用规律的图表
  • 规律识别:从数据中提炼的 2—3 个重要洞察
  • 研究建议:具体的定性与定量后续研究方向
  • 分析脚本(如有需要):可复现分析的 Python 代码
  • 后续行动:基于发现的优先级行动清单

延伸阅读

© killvxk, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in pm-data-analytics/skills/cohort-analysis of killvxk/pm-skills-zh.

Open the folder on GitHubat commit 5179784

Compare with similar skills

Cohort Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Cohort Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Cohort Analysis this skillkillvxk/pm-skills-zh168—~562Automated safety check: PassMIT
Retentioneering Contributingretentioneering/retentioneering-tools920—~1.8kAutomated safety check: PassApache-2.0
Retentioneering Product Analyticsretentioneering/retentioneering-tools920—~1.6kAutomated safety check: PassApache-2.0
A/B Test Analysisphuryn/pm-skills27k—~893Automated safety check: PassMIT
Batch CohortAperivue/medsci-skills329—~2.4kAutomated safety check: PassMIT
Opik Analytics Instrumentationcomet-ml/opik22k—~4.4kAutomated safety check: PassApache-2.0

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Works with

Questions about Cohort Analysis

What does Cohort Analysis do?

对用户参与度数据执行同期群分析——留存曲线、功能采用趋势及分层洞察。适用于按同期群分析用户留存、研究功能随时间的采用情况、调查流失规律,或识别参与度趋势。. Cohort Analysis is an agent skill from killvxk/pm-skills-zh.

When should I use Cohort Analysis?

Cohort Analysis fits situations like: tasks that involve Product analytics.

How do I install Cohort Analysis in Claude Code?

Run `npx skills add killvxk/pm-skills-zh --skill cohort-analysis -a claude-code`. Or copy the skill folder (pm-data-analytics/skills/cohort-analysis in killvxk/pm-skills-zh) into .claude/skills/cohort-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Cohort Analysis in Codex?

Run `npx skills add killvxk/pm-skills-zh --skill cohort-analysis -a codex`. Or copy the skill folder (pm-data-analytics/skills/cohort-analysis in killvxk/pm-skills-zh) into .agents/skills/cohort-analysis in your project. Codex loads it when a task matches its description.

Can I use Cohort Analysis in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add killvxk/pm-skills-zh --skill cohort-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cohort-analysis, .gemini/skills/cohort-analysis, .github/skills/cohort-analysis and .opencode/skills/cohort-analysis in your project.

What does Cohort Analysis need to run?

SKILL.md names no scripts, command-line tools or credentials: Cohort Analysis is instructions for the agent only. Our summary lists: Python 3.

Does Cohort Analysis access the network?

SKILL.md names 1 domain. As links in the text: productcompass.pm. This is read from the text; nothing was executed.

Is Cohort Analysis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Cohort Analysis use?

Cohort Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cohort Analysis use?

About 562 tokens (SKILL.md is roughly 2.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Cohort Analysis?

Skills that share tags, products or a category with Cohort Analysis: Retentioneering Contributing (retentioneering/retentioneering-tools, 920 stars), Retentioneering Product Analytics (retentioneering/retentioneering-tools, 920 stars), A/B Test Analysis (phuryn/pm-skills, 27k stars) and Batch Cohort (Aperivue/medsci-skills, 329 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cohort Analysis?

killvxk (a GitHub user) maintains it in killvxk/pm-skills-zh, which has 168 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on March 16, 2026.

Source: killvxk/pm-skills-zh on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.