How do I install the Dstack Funnel skill?

Run npx skillmds@latest add upsolve-labs/dstack-funnel in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Dstack Funnel safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Dstack Funnel?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Dstack Funnel free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Dstack Funnel?

Upsolve-Labs (@upsolve-labs) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Dstack Funnel by upsolve-labs — Agent Skill

Name: Dstack Funnel
Author: Upsolve-Labs

Dstack Funnel

Funnel drop-off analysis. Define conversion steps and get conversion rates, absolute drop-off counts, and segment breakdowns at each stage. Use for product analytics, marketing funnels, checkout flows, or any sequential user journey. Trigger phrases: "funnel analysis", "where are users dropping off?", "conversion rate", "show me the funnel", "why aren't users converting?".

Upsolve-Labs b1ab128 3.4 KB Updated Sep 17, 2026

File contents

Update Check (run first)

_UPD=$(~/.claude/skills/data-stack/bin/data-stack-update-check 2>/dev/null || .claude/skills/data-stack/bin/data-stack-update-check 2>/dev/null || true)
[ -n "$_UPD" ] && echo "$_UPD" || true

If output shows UPGRADE_AVAILABLE <old> <new>: read ~/.claude/skills/data-stack/skills/dstack-upgrade/SKILL.md and follow the "Inline upgrade flow". If JUST_UPGRADED <from> <to>: tell user "Running data-stack v{to} (just updated!)" and continue.

/funnel

You are helping the user analyze a conversion funnel.

Before Starting

AskUserQuestion: "What are the steps in your funnel, in order? (e.g. 'page view → add to cart → checkout started → purchase'). Also specify the time window (e.g. 'last 30 days')."

Phase 1: Overall Funnel

Open an Upsolve thread:

analyze_data("Show me a funnel analysis for these steps: <steps>. For each step show: user count, conversion rate from the previous step, and overall conversion rate from the top of the funnel. Time window: <window>.")

Phase 2: Identify Biggest Drop-off

Find the step with the largest absolute user drop. Dig in:

analyze_data("At the <biggest drop-off step> step, show me what users who did NOT proceed to the next step have in common. Look at behavioral patterns, cohort, acquisition source, or any other available attributes.", thread_id=<id>)

Phase 3: Segment the Funnel

analyze_data("Break down the full funnel by the top 2–3 relevant dimensions (e.g. device type, acquisition channel, geography, user segment). Which segments have the best and worst end-to-end conversion rates?", thread_id=<id>)

Phase 4: Output Funnel Report

FUNNEL ANALYSIS: <name or description>
Period: <time window>
────────────────────────────────────────────────────────────
Step                     Users       Step Conv%    Overall%
────────────────────────────────────────────────────────────
→ <Step 1>              XX,XXX        —             100%
→ <Step 2>              XX,XXX       XX%            XX%
→ <Step 3>              XX,XXX       XX%            XX%   ← biggest drop
→ <Step 4>              XX,XXX       XX%            XX%

Overall conversion: XX%

TOP SEGMENTS (by end-to-end conversion):
  Best:  <segment> — XX%
  Worst: <segment> — XX%

BIGGEST OPPORTUNITY:
  Improving <step> conversion by 10% would add ~XXX completions/month.

DROP-OFF PROFILE at <step>:
  <key patterns in users who didn't convert>

Rules

Always identify the single biggest drop-off step — it's the most actionable finding.
Include absolute user counts, not just percentages.
If funnel steps are ambiguous from the data, ask the user to clarify before proceeding.
"Biggest opportunity" estimate should be based on current volume, not invented.

---name: dstack-funneldescription: Funnel drop-off analysis. Define conversion steps and get conversion rates, absolute drop-off counts, and segment breakdowns at each stage. Use for product analytics, marketing funnels, checkout flows, or any sequential user journey. Trigger phrases: "funnel analysis", "where are users dropping off?", "conversion rate", "show me the funnel", "why aren't users converting?".license: MIT---## Update Check (run first)```bash_UPD=$(~/.claude/skills/data-stack/bin/data-stack-update-check 2>/dev/null || .claude/skills/data-stack/bin/data-stack-update-check 2>/dev/null || true)[ -n "$_UPD" ] && echo "$_UPD" || true```If output shows `UPGRADE_AVAILABLE <old> <new>`: read `~/.claude/skills/data-stack/skills/dstack-upgrade/SKILL.md` and follow the "Inline upgrade flow". If `JUST_UPGRADED <from> <to>`: tell user "Running data-stack v{to} (just updated!)" and continue.# /funnelYou are helping the user analyze a conversion funnel.## Before StartingAskUserQuestion: "What are the steps in your funnel, in order? (e.g. 'page view → add to cart → checkout started → purchase'). Also specify the time window (e.g. 'last 30 days')."## Phase 1: Overall FunnelOpen an Upsolve thread:```analyze_data("Show me a funnel analysis for these steps: <steps>. For each step show: user count, conversion rate from the previous step, and overall conversion rate from the top of the funnel. Time window: <window>.")```## Phase 2: Identify Biggest Drop-offFind the step with the largest absolute user drop. Dig in:```analyze_data("At the <biggest drop-off step> step, show me what users who did NOT proceed to the next step have in common. Look at behavioral patterns, cohort, acquisition source, or any other available attributes.", thread_id=<id>)```## Phase 3: Segment the Funnel```analyze_data("Break down the full funnel by the top 2–3 relevant dimensions (e.g. device type, acquisition channel, geography, user segment). Which segments have the best and worst end-to-end conversion rates?", thread_id=<id>)```## Phase 4: Output Funnel Report```FUNNEL ANALYSIS: <name or description>Period: <time window>────────────────────────────────────────────────────────────Step Users Step Conv% Overall%────────────────────────────────────────────────────────────→ <Step 1> XX,XXX — 100%→ <Step 2> XX,XXX XX% XX%→ <Step 3> XX,XXX XX% XX% ← biggest drop→ <Step 4> XX,XXX XX% XX%Overall conversion: XX%TOP SEGMENTS (by end-to-end conversion): Best: <segment> — XX% Worst: <segment> — XX%BIGGEST OPPORTUNITY: Improving <step> conversion by 10% would add ~XXX completions/month.DROP-OFF PROFILE at <step>: <key patterns in users who didn't convert>```## Rules- Always identify the single biggest drop-off step — it's the most actionable finding.- Include absolute user counts, not just percentages.- If funnel steps are ambiguous from the data, ask the user to clarify before proceeding.- "Biggest opportunity" estimate should be based on current volume, not invented.

Frequently asked questions