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.
Structure a retention analysis, churn investigation, or engagement deep-dive for any product team.
Install Retention Analysis
$ npx skills add mohitagw15856/pm-claude-skills --skill retention-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mohitagw15856/pm-claude-skills retention-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/retention-analysis .claude/skills/retention-analysis && rm -rf skills-srcUse ~/.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/
Install the "retention-analysis" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/retention-analysis into .claude/skills/retention-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "retention-analysis", 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 install https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/retention-analysisType 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.
$ npx skills add mohitagw15856/pm-claude-skills --skill retention-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mohitagw15856/pm-claude-skills retention-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/retention-analysis .agents/skills/retention-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "retention-analysis" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/retention-analysis into .agents/skills/retention-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "retention-analysis", 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.
$ npx skills add mohitagw15856/pm-claude-skills --skill retention-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mohitagw15856/pm-claude-skills retention-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/retention-analysis .cursor/skills/retention-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "retention-analysis" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/retention-analysis into .cursor/skills/retention-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "retention-analysis", 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 https://github.com/mohitagw15856/pm-claude-skills.git --path skills/retention-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mohitagw15856/pm-claude-skills --skill retention-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mohitagw15856/pm-claude-skills retention-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/retention-analysis .gemini/skills/retention-analysis && rm -rf skills-srcUse ~/.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/
Install the "retention-analysis" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/retention-analysis into .gemini/skills/retention-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "retention-analysis", 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.
$ gh skill install mohitagw15856/pm-claude-skills retention-analysisInstalls 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).
$ npx skills add mohitagw15856/pm-claude-skills --skill retention-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/retention-analysis .github/skills/retention-analysis && rm -rf skills-srcUse ~/.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/
Install the "retention-analysis" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/retention-analysis into .github/skills/retention-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "retention-analysis", 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.
$ npx skills add mohitagw15856/pm-claude-skills --skill retention-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mohitagw15856/pm-claude-skills retention-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/retention-analysis .opencode/skills/retention-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "retention-analysis" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/retention-analysis into .opencode/skills/retention-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "retention-analysis", 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
retention-analysis- GitHub stars
- 1.4k
- Token cost
- ~1.9k tokens
- SKILL.md length
- 929 words
- Files
- 4 (incl. references)
- Skills in repo
- 1,348
- Repo updated
- First seen
- Licence
- MIT
At a glance
Structure a retention analysis, churn investigation, or engagement deep-dive for any product team.
- Works in 4 steps: Segment the problem → Find the inflection points → Identify the "aha moment" correlation → …
- Asked to analyse user retention
- SKILL.md covers Retention Fundamentals, Retention Metrics Definitions, Retention Investigation… and Output Format, plus 7 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Retention Analysis is an agent skill from mohitagw15856/pm-claude-skills. Structure a retention analysis, churn investigation, or engagement deep-dive for any product team. Use when asked to analyse user retention, investigate churn, measure DAU/MAU, or build a retention improvement plan. Produces a retention snapshot with root cause hypotheses, aha-moment correlation, and prioritised interventions.
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/curve-reading.md`, `references/worked-example.md` and `templates/retention-readout.md`).
It sits in Data & Analytics, covering Product analytics. The repository describes itself as: 1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in… The licence is MIT.
When your agent uses it
- Asked to analyse user retention
- Investigate churn
- Measure DAU/MAU
- Build a retention improvement plan
Example prompts
- “/retention-analysis”
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 1cbf1f0. 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
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
Retention Analysis loads about 1.9k tokens when it runs, and up to ~4.3k if it reads all its reference files. Until then it costs about 87 tokens; SKILL.md has 929 words of instructions outside code blocks.
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 mohitagw15856/pm-claude-skills at commit 1cbf1f0, republished under its MIT licence (© mohitagw15856). 929 words, ~1,851 tokens.
Download SKILL.mdSave it as
.claude/skills/retention-analysis/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- retention-analysis
- description
- Structure a retention analysis, churn investigation, or engagement deep-dive for any product team. Use when asked to analyse user retention, investigate churn, measure DAU/MAU, or build a retention improvement plan. Produces a retention snapshot with root cause hypotheses, aha-moment correlation, and prioritised interventions.
Retention Analysis Skill
Diagnose why users leave, identify what keeps them, and recommend specific, testable interventions — not vague "improve onboarding" suggestions.
Retention Fundamentals
The retention curve has two components:
- Steepness of initial drop (D1–D7) — onboarding problem
- Long-term floor level — product-market fit indicator
A product with PMF has a retention curve that flattens. If it trends to zero, you have a PMF problem, not an onboarding problem. Name this distinction explicitly.
Retention Metrics Definitions
| Metric | Formula | What It Tells You |
|---|---|---|
| D1 Retention | Users who return on day 2 ÷ new users day 1 | Quality of first experience |
| D7 Retention | Users active on day 8 ÷ users who joined 7 days ago | Early habit formation |
| D30 Retention | Users active on day 31 ÷ users who joined 30 days ago | Product-market fit signal |
| DAU/MAU Ratio | Daily active users ÷ monthly active users | Stickiness (>20% good, >50% excellent) |
| Churn Rate | Users lost in period ÷ users at start of period | Monthly or annual |
| Net Revenue Retention | MRR at end of period ÷ MRR at start (same cohort) | Revenue health including expansion |
Retention Investigation Framework
Step 1: Segment the problem
Don't analyse "retention" — analyse retention for specific cohorts:
- New vs returning users
- Paid vs free
- Acquisition channel (organic vs paid vs referral)
- Onboarding path completed vs not
- Feature usage (power users vs lurkers)
Step 2: Find the inflection points
Where does the drop happen? D1? D7? Month 3?
- D1 drop → First session experience
- D7 drop → Habit loop not formed
- D30 drop → Value not delivered at depth
- Month 3+ drop → Boredom, competition, or lifecycle event
Step 3: Identify the "aha moment" correlation
Which early behaviour predicts long-term retention?
- Run correlation: users who did [X] in first 7 days vs 30-day retention
- Common patterns: connected an integration, invited a teammate, completed a core action N times
Step 4: Qualify the churn
Interview churned users — never skip this. Survey data alone is insufficient.
- "What was the trigger that led you to cancel/stop?"
- "What were you trying to accomplish that you couldn't?"
- "What would need to change for you to come back?"
Output Format
Retention Analysis — [Product/Segment] — [Date]
Question: [Specific retention question being answered] Period Analysed: [Date range] Segment: [Which users]
Current Retention Snapshot:
| Metric | Current | Industry Benchmark | Status |
|---|---|---|---|
| D1 Retention | [X%] | 25–40% | 🔴/🟡/🟢 |
| D7 Retention | [X%] | 10–25% | 🔴/🟡/🟢 |
| D30 Retention | [X%] | 5–15% | 🔴/🟡/🟢 |
| DAU/MAU | [X%] | 10–20% typical | 🔴/🟡/🟢 |
Retention Curve Shape: [Flattening / Still declining / Trending to zero] PMF Signal: [Strong / Weak / Absent — based on curve shape]
Root Cause Hypotheses:
| Hypothesis | Evidence | Confidence | Test |
|---|---|---|---|
| [Cause] | [Data point] | H/M/L | [How to validate] |
"Aha Moment" Correlation: Users who [specific action] in first [N] days retain at [X%] vs [Y%] for those who don't.
Recommended Interventions:
| Intervention | Target Drop | Expected Lift | Effort | Priority |
|---|---|---|---|---|
| [Specific change] | D1 / D7 / D30 | [X%] | S/M/L | 1/2/3 |
Monitoring Plan:
- Metric to track: [X]
- Review cadence: [Weekly / Monthly]
- Alert threshold: [If X drops below Y, investigate immediately]
Required Inputs
Ask the user for these if not provided:
- Product and business model (SaaS / consumer app / marketplace / other)
- Current retention metrics (D1, D7, D30 if available)
- Segment to analyse (all users / paid / free / a specific cohort)
- Key question to answer (why is retention dropping? what drives retention?)
- Available data (analytics events, churn surveys, interview notes)
Show full SKILL.md (403 more words)Show less
Deeper Materials
This skill ships with support files — use them when they are available:
references/curve-reading.md— Reading Retention Curves Without Fooling Yourself. Apply it while producing the output; it carries the calibration and judgment calls the method summary above compresses.templates/retention-readout.md— a fill-in version of the deliverable with the quality gates inline. Offer it when the user wants to work the document themselves rather than have it generated.
Scoring Rubric (0–40)
Score any output of this skill before handing it over; 32+ is ship-quality.
| Dimension | 0 | 5 | 10 |
|---|---|---|---|
| Curve diagnosis | Reports a retention number without curve shape | Shape shown but not interpreted | Flattening vs trending-to-zero explicitly diagnosed and tied to what it means (PMF vs onboarding problem) |
| Cohort discipline | All users lumped into one blended rate | Cohorts split but read as a table dump | Cohorts segmented before analysis, with the divergent cohort called out and explained |
| Aha-moment linkage | Activation never connects to retention | Correlation claimed without data or caveat | The behavior separating retained from churned users identified with evidence, or honestly flagged unknown with a plan to find it |
| Intervention specificity | "Improve onboarding"-grade advice | Specific actions but no measurement plan | Interventions name the user moment they target, plus a monitoring plan with an alert threshold and churned-user interviews |
Quality Checks
- Retention curve shape is diagnosed (flattening vs trending to zero = PMF vs onboarding)
- Cohorts are segmented before analysis (not all users lumped together)
- "Aha moment" correlation is identified or flagged as unknown
- Interventions are specific (not "improve onboarding")
- Churned user interviews are recommended (not just data analysis)
- Monitoring plan includes an alert threshold
Anti-Patterns
- Do not recommend "improve onboarding" without specifying what specific step to change and why
- Do not analyse retention without segmenting by cohort — aggregate retention curves hide cohort-specific patterns
- Do not treat DAU/MAU below 5% as a retention problem — at that level, it is a product-market fit problem
- Do not skip qualitative research — churned user interviews reveal reasons that quantitative data cannot
- Do not set a monitoring alert without specifying the threshold that triggers it
Guidelines
- Never recommend "improve onboarding" without specifying what to change and why
- Benchmark against industry — consumer apps, SaaS, and marketplaces have very different retention norms
- If DAU/MAU is below 5%, that's a PMF conversation, not a retention tactics conversation
- Always recommend talking to churned users — no amount of data replaces understanding the reason
Example Trigger Phrases
- "Analyse user retention."
- "Investigate churn."
- "Build a retention improvement plan."
© mohitagw15856, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (references) in skills/retention-analysis of mohitagw15856/pm-claude-skills.
- SKILL.md
- references/curve-reading.md
- references/worked-example.md
- templates/retention-readout.md
Open the folder on GitHubat commit 1cbf1f0
Compare with similar skills
Retention 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Retention Analysis this skillmohitagw15856/pm-claude-skills | 1.4k | — | ~1.9k | Automated safety check: Pass | MIT | |
| PostHog CLI Queriesdebugtheworldbot/keyStats | 1.5k | — | ~1.2k | Automated safety check: Pass | MIT | |
| Retentioneering Contributingretentioneering/retentioneering-tools | 927 | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| Retentioneering Product Analyticsretentioneering/retentioneering-tools | 927 | — | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Feature Analytics Instrumentation Plannermistralai/mistral-vibe | 5.1k | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | |
| Funnel Analysisliangdabiao/claude-data-analysis-ultra-main | 290 | 1 repos | ~781 | Automated safety check: Notes | None |
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Related
Categories
Questions about Retention Analysis
What does Retention Analysis do?
Structure a retention analysis, churn investigation, or engagement deep-dive for any product team. Retention Analysis is an agent skill from mohitagw15856/pm-claude-skills. Structure a retention analysis, churn investigation, or engagement deep-dive for any product team.
When should I use Retention Analysis?
Retention Analysis fits situations like: asked to analyse user retention; investigate churn; measure DAU/MAU; build a retention improvement plan.
How do I install Retention Analysis in Claude Code?
Run `npx skills add mohitagw15856/pm-claude-skills --skill retention-analysis -a claude-code`. Or copy the skill folder (skills/retention-analysis in mohitagw15856/pm-claude-skills) into .claude/skills/retention-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Retention Analysis in Codex?
Run `npx skills add mohitagw15856/pm-claude-skills --skill retention-analysis -a codex`. Or copy the skill folder (skills/retention-analysis in mohitagw15856/pm-claude-skills) into .agents/skills/retention-analysis in your project. Codex loads it when a task matches its description.
Can I use Retention 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 mohitagw15856/pm-claude-skills --skill retention-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/retention-analysis, .gemini/skills/retention-analysis, .github/skills/retention-analysis and .opencode/skills/retention-analysis in your project.
What does Retention Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Retention Analysis is instructions for the agent only.
Does Retention Analysis 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 Retention 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 Retention Analysis use?
Retention 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 Retention Analysis use?
About 1.9k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.4k tokens, read only when the agent opens those files.
What are the alternatives to Retention Analysis?
Skills that share tags, products or a category with Retention Analysis: PostHog CLI Queries (debugtheworldbot/keyStats, 1.5k stars), Retentioneering Contributing (retentioneering/retentioneering-tools, 927 stars), Retentioneering Product Analytics (retentioneering/retentioneering-tools, 927 stars) and Feature Analytics Instrumentation Planner (mistralai/mistral-vibe, 5.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Retention Analysis?
mohitagw15856 (a GitHub user) maintains it in mohitagw15856/pm-claude-skills, which has 1,434 GitHub stars. The repository holds 1,348 skills in this directory. The repository was last updated on October 9, 2026.
Source: mohitagw15856/pm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.