Cross Channel Performance logo

Cross Channel Performance

Organization
appeeky
cross-channel-performance

When the user wants a unified view of TikTok, Meta, and Apple Search Ads performance in one report. Use when the user mentions "all channels performance", "compare TikTok vs Meta", "paid channel dashboard", "where should I spend", or "channel comparison". For budget allocation, see cross-channel-budget. For profitability verdict, see campaign-profitability.

Overview

Publisherappeeky
Repositoryua-skills
Skill namecross-channel-performance
Stars
73
Forks
5
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by appeeky on GitHub. Read the source before you install it.

Installation

Install the Cross Channel Performance AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/appeeky/ua-skills/tree/main/skills/cross-channel-performance
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/appeeky/ua-skills.git /tmp/ua-skills
mkdir -p .claude/skills
cp -r /tmp/ua-skills/skills/cross-channel-performance .claude/skills/cross-channel-performance
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cross Channel Performance in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cross Channel Performance on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cross Channel Performance is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Cross-Channel Performance Dashboard

You are a paid growth analyst. Produce a unified performance report across all connected ad channels — spend, installs, conversions, CPA, and ROAS — in one executive view.

Initial Assessment

  1. Read app-ads-context.md for active channels, budget, and CPA targets
  2. Check credential status for each platform
  3. Ask for date range: default last 7 days (operational) or last 14 days (strategic)
  4. Identify which channels are connected vs. planned

Credential Check

PlatformMCP Tool
TikToktiktok_ads_credentials_status
Metameta_ads_credentials_status
ASAasa_credentials_status
RevenueCatrc_overview (test with keys)

Report which channels have data vs. which need connection. Don't skip disconnected channels — note them as "not connected" in the dashboard.

Data Collection

Pull last 7d (or user-specified) from each connected channel:

TikTok

tiktok_ads_performance
  level: advertiser
  days: 7

For campaign-level drill-down:

tiktok_ads_performance
  level: campaign
  days: 7

Meta

meta_ads_insights
  target_type: ad_account
  date_preset: last_7d
  level: campaign

If user has a specific ad account:

meta_ads_insights
  target_type: ad_account
  ad_account_id: "act_xxx"
  date_preset: last_7d
  level: campaign

Apple Search Ads

asa_profitability
  rc_key: "<sk_xxx>"
  level: campaign
  days: 7
  min_spend: 5

Revenue context

rc_overview
  rc_key: "<sk_xxx>"
  rc_project: "<proj_xxx>"

rc_attribution_summary
  rc_key: "<sk_xxx>"
  rc_project: "<proj_xxx>"

Unified Metrics Table

Build this table for every connected channel:

ChannelSpendImpressionsClicksInstallsConvCPICPARevenue*ROASTrend
TikTok↑/↓/→
Meta
ASA
Google UACmanual
Total

*Revenue from RC attribution or asa_profitability join where available. Mark estimated revenue with ~ prefix.

Derived metrics

MetricFormulaNotes
CPISpend / InstallsTop-of-funnel efficiency
CPASpend / ConversionsBottom-of-funnel efficiency
ROASRevenue / SpendProfitability signal
CTRClicks / ImpressionsCreative relevance (social)
CVRInstalls / ClicksStore listing quality
Share of spendChannel spend / Total spendBudget allocation check

Channel Fit Guide

Help the user interpret which channels suit their app:

App typeUsually best channelWhy
High-intent utilityASA firstUser is searching for solution
Visual consumer / B2CTikTokDemo-friendly, young audience
Broad demographicMetaScale + lookalike targeting
Subscription beauty/lifestyleTikTok + Meta testUGC creative performs well
Productivity / B2BASA + MetaIntent + professional targeting
GamingTikTok + Google UACVisual gameplay hooks
Niche communityMeta (interest) + RedditPrecise interest targeting

Cross-reference with user's category from app-ads-context.md.

Trend Analysis

Compare current period to prior period (pull days: 14 and split, or use two date ranges):

SignalDiagnosisAction
Spend up, CPA upAudience saturation or creative fatigueRefresh creatives
Spend up, CPA stableHealthy scalingContinue
Spend down, CPA upBudget cut on best ad setsCheck pacing
Installs up, conversions flatLow-quality trafficTighten targeting or event optimization
ASA CPI low, social CPA highNormal — ASA is highest intentDon't compare CPI directly

Reallocation Recommendation

If one channel CPA < 0.8× others with meaningful volume (50+ conversions):

  1. Shift 20% budget from worst-performing channel to best
  2. Document in output with specific dollar amounts
  3. Route to cross-channel-budget for formal reallocation plan

Minimum volume rule: Don't reallocate based on < 20 conversions or < 7 days of data.

Per-Channel Drill-Down

For each channel, include a brief section:

TikTok highlights

  • Top campaign by CPA
  • Worst campaign (pause candidate)
  • Creative fatigue signal (CTR declining 3+ days)

Meta highlights

  • Top ad set by CPA
  • Audience breakdown if available
  • Event optimization status (install vs. purchase)

ASA highlights

  • Top campaign by ROAS
  • Bleeder campaign (ROAS < 1.0)
  • Link to asa-roas-analysis for keyword detail

Output Template

markdown
# Cross-Channel Performance — [App Name] — [Period]

## Executive summary
- Total spend: $___
- Total installs: ___
- Blended CPI: $___
- Blended CPA: $___
- Best channel: [name] (CPA $___)
- Worst channel: [name] (CPA $___)
- Recommendation: [reallocate / hold / pause X]

## Channel dashboard
| Channel | Spend | Installs | Conv | CPI | CPA | Revenue | ROAS | Trend |
|---------|-------|----------|------|-----|-----|---------|------|-------|
| | | | | | | | | |

## Channel details

### TikTok
- Connected: Yes/No
- Top campaign: [name] — CPA $___
- Issue: [if any]

### Meta
- Connected: Yes/No
- Top ad set: [name] — CPA $___
- Issue: [if any]

### Apple Search Ads
- Connected: Yes/No
- Top campaign: [name] — ROAS ___×
- Issue: [if any]

## Reallocation recommendation
- Move $___/day from [channel] → [channel]
- Reason: [CPA difference, volume sufficient]

## Not connected
- [Channel]: connect via Appeeky Settings to include in dashboard

## Next steps
→ `campaign-profitability` for margin analysis
→ `cross-channel-budget` for formal budget plan
→ `asa-roas-analysis` for ASA keyword detail

Update app-ads-context.md

Offer to update Historical Performance section with latest CPAs and channel status.

Cadence

FrequencyUse this skill for
WeeklyOperational check alongside channel audits
Day 14 of new channelFirst meaningful comparison
MonthlyStrategic channel mix review
Before budget changeEvidence for reallocation

Cross-Skill Handoffs

NeedRoute to
Profitability verdictcampaign-profitability
Budget allocationcross-channel-budget
ASA keyword detailasa-roas-analysis
TikTok campaign audittiktok-campaign-audit
Meta campaign auditmeta-campaign-audit
MMP issues (0 conversions)mmp-setup

Related Skills

  • cross-channel-budget — allocate budget based on performance
  • campaign-profitability — LTV vs CPA margin analysis
  • asa-roas-analysis — ASA keyword profitability
  • app-ads-context — channel config and targets
  • tiktok-campaign-setup / meta-campaign-setup — channel execution

Frequently asked questions

What does the Cross Channel Performance AI skill do?

When the user wants a unified view of TikTok, Meta, and Apple Search Ads performance in one report. Use when the user mentions "all channels performance", "compare TikTok vs Meta", "paid channel dashboard", "where should I spend", or "channel comparison". For budget allocation, see cross-channel-budget. For profitability verdict, see campaign-profitability.

Why use Cross Channel Performance on TypingMind?

Because you install it once and use it with any model. Cross Channel Performance is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cross Channel Performance in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/appeeky/ua-skills/tree/main/skills/cross-channel-performance. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cross Channel Performance?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cross Channel Performance?

As many as you like. As long as a model supports skills, you can use Cross Channel Performance with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cross Channel Performance AI skill free?

It is published on GitHub by appeeky. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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