name: landing-page-optimizer
description: Optimize conversion pages for paid traffic from Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads journeys.
Ads Landing Page Optimizer
Purpose
Core mission:
conversion uplift design, CTA testing, page iteration planThis skill is specialized for advertising workflows and should output actionable plans rather than generic advice.
When To Trigger
Use this skill when the user asks for:
ad execution guidance tied to business outcomes
growth decisions involving revenue, roas, cpa, or budget efficiency
platform-level actions for: Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads
this specific capability: conversion uplift design, CTA testing, page iteration planHigh-signal keywords:
ads, advertising, campaign, growth, revenue, profit
roas, cpa, roi, budget, bidding, traffic, conversion, funnel
meta, googleads, tiktokads, youtubeads, amazonads, shopifyads, dspInput Contract
Required:
objective: growth target and KPI priority
budget_frame: test budget and scale budget
channel_scope: channels to includeOptional:
audience_segments
creative_inventory
seasonality_window
policy_constraintsOutput Contract
1. Strategy Snapshot
2. Channel Role Definition
3. Budget and Bidding Plan
4. Test Matrix
5. Scale and Kill Rules
Workflow
1. Define objective hierarchy (primary and secondary KPI).
2. Assign channel roles by funnel stage.
3. Allocate budget by expected signal and risk.
4. Design test cells and learning windows.
5. Set scale, hold, and stop rules.
Decision Rules
If KPI conflict exists, prioritize revenue efficiency over volume.
If channel evidence is weak, allocate minimum test budget first.
If audience is broad, start with modular creatives and layered targeting.Platform Notes
Primary scope:
Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify AdsPlatform behavior guidance:
Keep recommendations channel-aware; do not collapse all channels into one generic plan.
For Meta and TikTok Ads, prioritize creative testing cadence.
For Google Ads and Amazon Ads, prioritize demand-capture and query/listing intent.
For DSP/programmatic, prioritize audience control and frequency governance.Constraints And Guardrails
Never fabricate metrics or policy outcomes.
Separate observed facts from assumptions.
Use measurable language for each proposed action.
Include at least one rollback or stop-loss condition when spend risk exists.Failure Handling And Escalation
If critical inputs are missing, ask for only the minimum required fields.
If platform constraints conflict, show trade-offs and a safe default.
If confidence is low, mark it explicitly and provide a validation checklist.
If high-risk issues appear (policy, billing, tracking breakage), escalate with a structured handoff payload.Code Examples
Strategy Matrix (YAML)
objective: improve_roas
channels:
- name: Meta
role: demand_creation
- name: Google Ads
role: demand_capture
budget_split:
Meta: 0.55
Google Ads: 0.45
Test Cell Example
cell_id: T1
variable: audience_segment
success_metric: cpa
Examples
Example 1: Channel mix reset
Input:
Budget fixed at 50k
ROAS dropped for two weeksOutput focus:
reallocation plan
test matrix
stop-loss conditionsExample 2: Creator-led expansion strategy
Input:
Goal: scale traffic without ROAS collapse
Channels: TikTok Ads + YouTube AdsOutput focus:
funnel role split
budget pacing logic
creative cadenceExample 3: Retargeting-heavy recovery
Input:
Prospecting unstable
Strong existing customer baseOutput focus:
retargeting architecture
audience exclusion design
two-phase launch planQuality Checklist
[ ] Required sections are complete and non-empty
[ ] Trigger keywords include at least 3 registry terms
[ ] Input and output contracts are operationally testable
[ ] Workflow and decision rules are capability-specific
[ ] Platform references are explicit and concrete
[ ] At least 3 practical examples are included