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funnel-ads-helper

Diagnose and optimize full conversion funnels for paid traffic from Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads campaigns.

danyangliu-sandwichlab0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install danyangliu-sandwichlab/funnel-ads-helper

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

Funnel Helper

Purpose

Core mission:

  • Analyze conversion funnel drop-off by stage.
  • Identify bottlenecks from ad click to checkout or lead submit.
  • Recommend stage-specific optimization actions.
  • Define funnel experiment roadmap and expected impact.

When To Trigger

Use this skill when the user asks for:

  • conversion funnel diagnosis
  • CVR optimization planning
  • landing page and checkout improvement sequence
  • funnel experiment design tied to ROAS/CPA goals

High-signal keywords:

  • conversion, funnel, checkout, cvr
  • cpa, roas, traffic, landing page
  • campaign, optimize, retarget

Input Contract

Required:

  • funnel_stage_metrics
  • traffic_source_breakdown
  • conversion_goal
  • observation_window

Optional:

  • session_replay_notes
  • form_or_checkout_logs
  • segment_breakdowns
  • experiment_history

Output Contract

  1. Funnel Stage Health Scorecard
  2. Bottleneck Priority Ranking
  3. Optimization Actions by Stage
  4. Experiment Roadmap with KPI impact
  5. Monitoring and Iteration Rules

Workflow

  1. Normalize funnel definitions and stage metrics.
  2. Rank drop-off severity and opportunity size.
  3. Map root causes (message mismatch, UX friction, trust gap, etc.).
  4. Recommend stage-specific actions and experiments.
  5. Define monitoring thresholds and iteration cadence.

Decision Rules

  • If top-funnel CTR is strong but CVR is weak, prioritize LP and checkout fixes.
  • If add-to-cart is strong but purchase is weak, prioritize trust/payment friction fixes.
  • If retargeting conversion is low, review audience freshness and offer relevance.
  • If funnel data is sparse, run diagnostic experiments before major redesign.

Platform Notes

Primary scope:

  • Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads

Platform behavior guidance:

  • Keep funnel interpretation tied to traffic intent by channel.
  • Distinguish ad-side and on-site bottlenecks before action.

Constraints And Guardrails

  • Do not infer funnel causes without stage-l...

Source information

Source
github
Repository
openclaw/skills
Path
skills/danyangliu-sandwichlab/funnel-ads-helper
Version
—
Commit
3edce7e5d0144cda5f062d2726a153a6a6d8a73f
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# Funnel Helper

## Purpose
Core mission:
- Analyze conversion funnel drop-off by stage.
- Identify bottlenecks from ad click to checkout or lead submit.
- Recommend stage-specific optimization actions.
- Define funnel experiment roadmap and expected impact.

## When To Trigger
Use this skill when the user asks for:
- conversion funnel diagnosis
- CVR optimization planning
- landing page and checkout improvement sequence
- funnel experiment design tied to ROAS/CPA goals

High-signal keywords:
- conversion, funnel, checkout, cvr
- cpa, roas, traffic, landing page
- campaign, optimize, retarget

## Input Contract
Required:
- funnel_stage_metrics
- traffic_source_breakdown
- conversion_goal
- observation_window

Optional:
- session_replay_notes
- form_or_checkout_logs
- segment_breakdowns
- experiment_history

## Output Contract
1. Funnel Stage Health Scorecard
2. Bottleneck Priority Ranking
3. Optimization Actions by Stage
4. Experiment Roadmap with KPI impact
5. Monitoring and Iteration Rules

## Workflow
1. Normalize funnel definitions and stage metrics.
2. Rank drop-off severity and opportunity size.
3. Map root causes (message mismatch, UX friction, trust gap, etc.).
4. Recommend stage-specific actions and experiments.
5. Define monitoring thresholds and iteration cadence.

## Decision Rules
- If top-funnel CTR is strong but CVR is weak, prioritize LP and checkout fixes.
- If add-to-cart is strong but purchase is weak, prioritize trust/payment friction fixes.
- If retargeting conversion is low, review audience freshness and offer relevance.
- If funnel data is sparse, run diagnostic experiments before major redesign.

## Platform Notes
Primary scope:
- Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads

Platform behavior guidance:
- Keep funnel interpretation tied to traffic intent by channel.
- Distinguish ad-side and on-site bottlenecks before action.

## Constraints And Guardrails
- Do not infer funnel causes without stage-l...

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