Agent skill

Product Analytics

Measure what matters with proper event tracking, funnels, cohorts, and metrics.

Install Product Analytics

skills CLI

$ npx skills add nicepkg/ai-workflow --skill product-analytics -a claude-code

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

GitHub CLI

$ gh skill install nicepkg/ai-workflow product-analytics --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/nicepkg/ai-workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/workflows/marketing-pro-workflow/.claude/skills/product-analytics .claude/skills/product-analytics && 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/

Paste into Claude Code

Install the "product-analytics" agent skill from https://github.com/nicepkg/ai-workflow/tree/main/workflows/marketing-pro-workflow/.claude/skills/product-analytics into .claude/skills/product-analytics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-analytics", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/nicepkg/ai-workflow/tree/main/workflows/marketing-pro-workflow/.claude/skills/product-analytics

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add nicepkg/ai-workflow --skill product-analytics -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install nicepkg/ai-workflow product-analytics --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/nicepkg/ai-workflow.git skills-src && mkdir -p .agents/skills && cp -r skills-src/workflows/marketing-pro-workflow/.claude/skills/product-analytics .agents/skills/product-analytics && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "product-analytics" agent skill from https://github.com/nicepkg/ai-workflow/tree/main/workflows/marketing-pro-workflow/.claude/skills/product-analytics into .agents/skills/product-analytics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-analytics", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add nicepkg/ai-workflow --skill product-analytics -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install nicepkg/ai-workflow product-analytics --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/nicepkg/ai-workflow.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/workflows/marketing-pro-workflow/.claude/skills/product-analytics .cursor/skills/product-analytics && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "product-analytics" agent skill from https://github.com/nicepkg/ai-workflow/tree/main/workflows/marketing-pro-workflow/.claude/skills/product-analytics into .cursor/skills/product-analytics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-analytics", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/nicepkg/ai-workflow.git --path workflows/marketing-pro-workflow/.claude/skills/product-analytics

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add nicepkg/ai-workflow --skill product-analytics -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install nicepkg/ai-workflow product-analytics --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/nicepkg/ai-workflow.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/workflows/marketing-pro-workflow/.claude/skills/product-analytics .gemini/skills/product-analytics && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "product-analytics" agent skill from https://github.com/nicepkg/ai-workflow/tree/main/workflows/marketing-pro-workflow/.claude/skills/product-analytics into .gemini/skills/product-analytics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-analytics", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install nicepkg/ai-workflow product-analytics

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add nicepkg/ai-workflow --skill product-analytics -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/nicepkg/ai-workflow.git skills-src && mkdir -p .github/skills && cp -r skills-src/workflows/marketing-pro-workflow/.claude/skills/product-analytics .github/skills/product-analytics && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "product-analytics" agent skill from https://github.com/nicepkg/ai-workflow/tree/main/workflows/marketing-pro-workflow/.claude/skills/product-analytics into .github/skills/product-analytics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-analytics", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add nicepkg/ai-workflow --skill product-analytics -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install nicepkg/ai-workflow product-analytics --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/nicepkg/ai-workflow.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/workflows/marketing-pro-workflow/.claude/skills/product-analytics .opencode/skills/product-analytics && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "product-analytics" agent skill from https://github.com/nicepkg/ai-workflow/tree/main/workflows/marketing-pro-workflow/.claude/skills/product-analytics into .opencode/skills/product-analytics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-analytics", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: product-analytics
GitHub stars: 285
Token cost: ~832 tokens
SKILL.md length: 113 words
Files: 2
Skills in repo: 61
Repo updated: Jan 20, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Measure what matters with proper event tracking, funnels, cohorts, and metrics.

Setting up analytics
SKILL.md covers North Star Metric, Key Metrics Hierarchy, Event Tracking and Funnel Analysis, plus 5 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
Tracking features

What it does

Product Analytics is an agent skill from nicepkg/ai-workflow. Measure what matters with proper event tracking, funnels, cohorts, and metrics. Use when setting up analytics, tracking features, or understanding behavior.

Its SKILL.md is about 830 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `manifest.yaml`).

It sits in Data & Analytics, covering Product analytics. The repository describes itself as: 🚀 170+ pre-built skills for Claude Code, Cursor, Codex & 14+ AI tools. Stop re-teaching your AI the same things. One command → instant domain expertise. Marketing, SEO, Trading… The licence is MIT.

When your agent uses it

Setting up analytics
Tracking features
Understanding behavior

Example prompts

“/product-analytics”

What it can do on your machine

Read from SKILL.md and the folder at commit d167b41. 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 (its code samples are yaml and typescript).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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

Product Analytics loads about 832 tokens when it runs. Until then it costs about 44 tokens; SKILL.md has 113 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~44
When it runs · the whole SKILL.md, loaded when a task matches: ~832

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 nicepkg/ai-workflow at commit d167b41, republished under its MIT licence (© nicepkg). 113 words, ~832 tokens.

Download SKILL.mdSave it as .claude/skills/product-analytics/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: product-analytics
description: Measure what matters with proper event tracking, funnels, cohorts, and metrics. Use when setting up analytics, tracking features, or understanding behavior.
license: Complete terms in LICENSE.txt

Product Analytics

Measure what matters and make data-driven decisions.

North Star Metric

The ONE metric that represents customer value

yaml

Examples:
  Slack: Weekly Active Users
  Airbnb: Nights Booked
  Spotify: Time Listening
  Shopify: GMV

Your North Star should: ✅ Represent customer value
  ✅ Correlate with revenue
  ✅ Be measurable frequently
  ✅ Rally the team

Key Metrics Hierarchy

North Star Metric
  ├── Input Metrics (drive North Star)
  │   ├── Acquisition
  │   ├── Activation
  │   └── Retention
  └── KPIs (business health)
      ├── Revenue
      ├── Churn
      └── LTV

Event Tracking

typescript

// Track user actions
analytics.track('Button Clicked', {
  button_name: 'signup',
  page: 'homepage',
  user_id: '123'
})

// Track page views
analytics.page('Homepage', {
  referrer: document.referrer,
  path: window.location.pathname
})

// Identify users
analytics.identify('user-123', {
  email: 'user@example.com',
  plan: 'pro',
  created_at: '2024-01-15'
})

Funnel Analysis

yaml

Sign-up Funnel:
  1. Land on homepage: 10,000 (100%)
  2. Click signup: 2,000 (20%)
  3. Fill form: 1,000 (10%)
  4. Verify email: 800 (8%)
  5. Complete onboarding: 400 (4%)

Insights:
  - Biggest drop: Homepage to signup (80% lost)
  - Fix: Clarify value prop, add social proof

Cohort Analysis

yaml

Week 1 Cohort (Jan 1-7):
  - D1: 80% active
  - D7: 40% active
  - D30: 20% active

Week 2 Cohort (Jan 8-14):
  - D1: 85% active (+5%)
  - D7: 50% active (+10%)
  - D30: 30% active (+10%)

Insight: Onboarding changes improved retention!

Retention Curves

yaml

Good Retention:
  - D1: 60-80%
  - D7: 40-60%
  - D30: 30-50%
  - Flattening curve (good!)

Bad Retention:
  - D1: 40%
  - D7: 10%
  - D30: 2%
  - Steep drop-off (bad!)

Key Metrics to Track

Acquisition

Traffic sources (organic, paid, referral)
Cost per click (CPC)
Conversion rate (visitor → signup)

Activation

Signup → first core action
Time to value
Onboarding completion rate

Retention

DAU / MAU (stickiness)
Retention rate D1, D7, D30
Churn rate

Revenue

MRR / ARR
ARPU (Average Revenue Per User)
LTV (Lifetime Value)
LTV:CAC ratio

Referral

Viral coefficient
Referral signups
NPS (Net Promoter Score)


## Tools

```yaml
Event Tracking:
  - Mixpanel (best for products)
  - Amplitude (good alternative)
  - PostHog (open-source)

Session Recording:
  - FullStory
  - LogRocket
  - Hotjar

A/B Testing:
  - Optimizely
  - VWO
  - Google Optimize (free)

Dashboard Design

yaml

Executive Dashboard:
  - North Star Metric (big number)
  - Revenue (MRR/ARR)
  - Key metric trends (graphs)

Product Dashboard:
  - Active users (DAU/WAU/MAU)
  - Feature usage
  - Retention cohorts
  - Funnels

Marketing Dashboard:
  - Traffic sources
  - Conversion rates
  - Cost per acquisition
  - ROI by channel

Summary

Great analytics:

✅ One North Star Metric
✅ Track everything
✅ Regular review (weekly)
✅ Share insights widely
✅ Act on data quickly

Files

SKILL.md and 1 other file in workflows/marketing-pro-workflow/.claude/skills/product-analytics of nicepkg/ai-workflow.

SKILL.md
manifest.yaml

Open the folder on GitHubat commit d167b41

Compare with similar skills

Product Analytics 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.

Product Analytics compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Product Analytics this skillnicepkg/ai-workflow	285	—	~832	Automated safety check: Pass	MIT	8 mo ago
PostHog CLI Queriesdebugtheworldbot/keyStats	1.5k	—	~1.2k	Automated safety check: Pass	MIT	5 days ago
Retentioneering Contributingretentioneering/retentioneering-tools	920	—	~1.8k	Automated safety check: Pass	Apache-2.0	yesterday
Retentioneering Product Analyticsretentioneering/retentioneering-tools	920	—	~1.6k	Automated safety check: Pass	Apache-2.0	yesterday
Retention Analysisliangdabiao/claude-data-analysis-ultra-main	290	1 repos	~1.3k	Automated safety check: Notes	None	5 mo ago
Feature Analytics Instrumentation Plannermistralai/mistral-vibe	5.1k	—	~2.2k	Automated safety check: Pass	Apache-2.0	yesterday

Similar skills

PostHog CLI Queries
debugtheworldbot/keyStats
Runs HogQL queries against this project's PostHog data from the terminal using posthog-cli, with bundled scripts for dashboard metadata the CLI itself has no command for.
1.5k GitHub stars~1.2k tokensUpdated 5 days ago
Data & AnalyticsAuto-check passed
Retentioneering Contributing
retentioneering/retentioneering-tools
Help the user turn their Retentioneering ideas, friction reports, bug findings, or feature needs into high-quality upstream contributions: from capturing and validating the idea, through minimal…
920 GitHub stars~1.8k tokensUpdated yesterday
Data & AnalyticsAuto-check passed
Retentioneering Product Analytics
retentioneering/retentioneering-tools
Analyze event logs, clickstreams, user paths, product funnels, retention, behavioral segments, transition graphs, step matrices, sequence patterns, and customer journeys using Retentioneering.
920 GitHub stars~1.6k tokensUpdated yesterday
Data & AnalyticsAuto-check passed
Retention Analysis
liangdabiao/claude-data-analysis-ultra-main
Analyze user retention and churn using survival analysis, cohort analysis, and machine learning.
290 GitHub starsUsed in 1 repo~1.3k tokens
Data & AnalyticsAuto-check: notes
Feature Analytics Instrumentation Planner
mistralai/mistral-vibe
Official
Plans which analytics events and properties a new feature needs, checks them against the existing event registry, and verifies them per environment.
5.1k GitHub stars~2.2k tokensUpdated yesterday
Data & AnalyticsAuto-check passed
Funnel Analysis
liangdabiao/claude-data-analysis-ultra-main
Analyze user conversion funnels, calculate step-by-step conversion rates, create interactive visualizations, and identify optimization opportunities.
290 GitHub starsUsed in 2 repos~781 tokens
Data & AnalyticsAuto-check: notes

Questions about Product Analytics

What does Product Analytics do?

Measure what matters with proper event tracking, funnels, cohorts, and metrics. Product Analytics is an agent skill from nicepkg/ai-workflow. Measure what matters with proper event tracking, funnels, cohorts, and metrics.

When should I use Product Analytics?

Product Analytics fits situations like: setting up analytics; tracking features; understanding behavior.

How do I install Product Analytics in Claude Code?

Run `npx skills add nicepkg/ai-workflow --skill product-analytics -a claude-code`. Or copy the skill folder (workflows/marketing-pro-workflow/.claude/skills/product-analytics in nicepkg/ai-workflow) into .claude/skills/product-analytics in your project. Claude Code loads it when a task matches its description.

How do I install Product Analytics in Codex?

Run `npx skills add nicepkg/ai-workflow --skill product-analytics -a codex`. Or copy the skill folder (workflows/marketing-pro-workflow/.claude/skills/product-analytics in nicepkg/ai-workflow) into .agents/skills/product-analytics in your project. Codex loads it when a task matches its description.

Can I use Product Analytics 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 nicepkg/ai-workflow --skill product-analytics -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/product-analytics, .gemini/skills/product-analytics, .github/skills/product-analytics and .opencode/skills/product-analytics in your project.

What does Product Analytics need to run?

SKILL.md names no scripts, command-line tools or credentials: Product Analytics is instructions for the agent only.

Does Product Analytics access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Product Analytics 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 Product Analytics use?

Product Analytics 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 Product Analytics use?

About 832 tokens (SKILL.md is roughly 3.3k 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 Product Analytics?

Skills that share tags, products or a category with Product Analytics: PostHog CLI Queries (debugtheworldbot/keyStats, 1.5k stars), Retentioneering Contributing (retentioneering/retentioneering-tools, 920 stars), Retentioneering Product Analytics (retentioneering/retentioneering-tools, 920 stars) and Retention Analysis (liangdabiao/claude-data-analysis-ultra-main, 290 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Product Analytics?

nicepkg (a GitHub organization) maintains it in nicepkg/ai-workflow, which has 285 GitHub stars. The repository holds 61 skills in this directory. The repository was last updated on January 20, 2026.

Source: nicepkg/ai-workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Product Analytics

Facts

At a glance

What it does

When your agent uses it

Example prompts

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Product Analytics

North Star Metric

Key Metrics Hierarchy

Event Tracking

Funnel Analysis

Cohort Analysis

Retention Curves

Key Metrics to Track

Acquisition

Activation

Retention

Revenue

Referral

Dashboard Design

Summary

Files

Compare with similar skills

Similar skills

More from nicepkg/ai-workflow

Related

Questions about Product Analytics