Skip to content
TrustedSkillsbeta
Back to all skills

Funnel Analysis

Checked
liangdabiao·vlatest·data

Analyzes funnel data to identify drop-off points and suggest improvements for conversion optimization.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add liangdabiao/claude-data-analysis-ultra-main --skill funnel-analysis -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

liangdabiao

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned liangdabiao/claude-data-analysis-ultra-main at 6b52856848.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
6b52856848
Manifest
.claude/skills/funnel-analysis/SKILL.md
Scanned
9 files, 1,731 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The funnel-analysis skill enables AI agents to perform comprehensive funnel analysis on structured datasets, identifying conversion bottlenecks and calculating drop-off rates across multiple stages. It processes tabular data to visualize user journeys and quantify efficiency at each step of a defined workflow.

When to use it

  • Analyze e-commerce checkout flows to pinpoint where customers abandon their carts.
  • Evaluate marketing campaign effectiveness by tracking lead progression from initial click to purchase.
  • Identify friction points in software onboarding processes using user activity logs.
  • Compare conversion rates between different traffic sources or product variants.

Key capabilities

  • Ingests and parses structured tabular data for analysis.
  • Calculates drop-off rates between consecutive funnel stages.
  • Generates visual representations of the user journey.
  • Identifies specific stages with the highest attrition.

Example prompts

  • "Analyze this sales dataset to create a funnel visualization showing conversion rates from lead generation to closed deal."
  • "Calculate the drop-off percentage at each stage of our customer onboarding process based on the provided CSV."
  • "Identify which marketing channel has the highest conversion efficiency by analyzing this traffic and revenue data."

Tips & gotchas

Ensure your input data is clean, tabular, and clearly labeled with distinct columns for each funnel stage. The skill relies on accurate row alignment; missing values in critical stages may skew drop-off calculations.