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Asa Weekly Optimization

Organization
appeeky
asa-weekly-optimization

When the user wants a weekly Apple Search Ads optimization routine — keyword bids, pauses, new opportunities, and budget pacing. Use when the user mentions "weekly ASA", "optimize Apple Search Ads", "ASA keywords", "ASA maintenance", or "ASA bid changes". For profitability analysis, see asa-roas-analysis. For automated scale playbook, see asa-admaxxing.

Overview

Publisherappeeky
Repositoryua-skills
Skill nameasa-weekly-optimization
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 Asa Weekly Optimization 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/asa-weekly-optimization
  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/asa-weekly-optimization .claude/skills/asa-weekly-optimization
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Asa Weekly Optimization 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 Asa Weekly Optimization 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 Asa Weekly Optimization 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.

ASA Weekly Optimization

You are an Apple Search Ads operator. Run a structured weekly maintenance cycle that turns performance data into specific keyword-level actions — bid changes, pauses, new keywords, and negatives.

Initial Assessment

  1. Read app-ads-context.md for target CPA, LTV, and active campaigns
  2. Check asa_credentials_status — stop if ASA not connected
  3. Ask which campaigns to optimize (or pull all active via asa_list_campaigns)
  4. Confirm date range: default last 7 days for actions, last 14 days for profitability

Weekly Schedule

DayFocusPrimary tools
MondayPull reports, check pacingasa_report_keywords, asa_report_search_terms
TuesdayProfitability analysisasa-roas-analysis at keyword level
WednesdayExecute bid/keyword changesasa_update_targeting_keywords, asa_create_targeting_keywords
ThursdayNegative keywordsasa-negative-keywords
FridayScale review + playbookasa_playbook_status, asa_admaxxing_recommendations

Compress to a single session if the user wants everything now — follow the same order.

Monday — Reports

Pull performance for each active campaign:

asa_report_keywords
  campaign_id: "<id>"
  days: 7

asa_report_search_terms
  campaign_id: "<id>"
  days: 7
  limit: 100

Pacing check

SignalAction
Campaign hits daily cap before 2pmIncrease daily budget 20% or raise cap
Campaign spends < 50% of budgetLower bids or expand keywords
Single keyword > 40% of spendDiversify or cap bid
Zero impressions on new keywordsRaise bid 20% or check match type

List campaigns with pacing issues before proceeding.

Tuesday — Profitability

Run asa-roas-analysis at level: keyword with days: 14. Use output to classify every keyword with $20+ spend:

BucketCriteriaWednesday action
ScaleROAS > target, impression share lowRaise bid 10%
HoldROAS near target, stableNo change
TrimROAS 0.7–1.0× targetLower bid 15%
PauseROAS < 0.7× target, $50+ spendPause keyword
PromoteSearch term ROAS > 1.5×, not a keyword yetAdd as exact match

Wednesday — Bid & Keyword Actions

Bid adjustment rules

SignalAction
ROAS < 1.0, spend > $50Lower bid 15% or pause
ROAS > 2.0, rank 5–15 (low share)Raise bid 10%
ROAS > 1.5, rank 1–3 (dominating)Hold — don't overbid
High impressions, 0 tapsCheck relevance; pause if TTR < 1%
100+ taps, 0 installsPause immediately
New high-intent search terms (from Monday)Add as exact match in category campaign

Execute changes

asa_update_targeting_keywords
  campaign_id: "<id>"
  ad_group_id: "<id>"
  # bid and status changes per keyword ID

asa_create_targeting_keywords
  campaign_id: "<id>"
  ad_group_id: "<id>"
  # new keywords from search term mining

asa_targeting_keyword_recommendations
  campaign_id: "<id>"
  ad_group_id: "<id>"

asa_bid_recommendations
  campaign_id: "<id>"
  ad_group_id: "<id>"
  keywords: ["meditation", "sleep tracker"]

Bid change limits: Never change more than 20% in one week on a single keyword unless pausing. Large swings destabilize Apple's auction learning.

Search term mining workflow

  1. Pull search terms report (Monday data)
  2. Filter: installs > 0 OR taps > 10
  3. Exclude terms already in exact match campaigns
  4. Add top performers as exact match in the appropriate campaign (brand / category / competitor)
  5. Add irrelevant terms to negatives (Thursday)

Thursday — Negatives

Route all wasted spend to asa-negative-keywords. Minimum criteria for negative candidates:

  • Spend > $20, zero installs (14 days)
  • Irrelevant intent (unrelated to app function)
  • Competitor brand not being targeted
  • Free/crack intent ("free", "hack", "mod apk")

Do not duplicate work — if running full weekly cycle, Thursday handles negatives only.

Friday — Scale Review

asa_playbook_status

asa_admaxxing_recommendations
  rc_key: "<sk_xxx>"
  app_id: "<apple_app_id>"
  level: "keyword"
  days: 14

Cross-check automated recommendations against Tuesday's profitability analysis. Apply recommendations that align with data; flag conflicts for user review.

Before any geo expansion:

asa_review_country_gate
  app_id: "<id>"
  min_rating: 4.5

Campaign-Type Playbook

Brand campaign

  • Goal: always win brand terms
  • Bid: high enough for 80%+ impression share
  • Action: rarely pause; if brand ROAS < 1.0, fix product page not bids

Category campaign

  • Goal: capture high-intent generic searches
  • Bid: moderate; scale winners from discovery
  • Action: test CPP per keyword cluster (aso-skills custom-product-pages)

Competitor campaign

  • Goal: conquest competitor brand searches
  • Bid: conservative; expect lower CVR
  • Action: pause terms with CPA > 2× target after $30 spend

Discovery campaign (Search Match)

  • Goal: find new keywords cheaply
  • Bid: lowest of all campaigns
  • Action: mine search terms weekly; never leave running without negatives

CPP / Creative Checks

If TTR < 3% on a high-volume ad group:

  1. Check if CPP is routed (aso-skills apple-search-ads CPS / custom product pages)
  2. Recommend new CPP variant matching keyword intent
  3. Re-test for 7 days before bid changes

Output Template

markdown
# ASA Weekly Optimization — [App Name] — Week of [Date]

## Campaign health
| Campaign | Spend (7d) | ROAS (14d) | Pacing | Status |
|----------|------------|------------|--------|--------|
| Brand | | | OK / Under / Over | |
| Category | | | | |
| Competitor | | | | |
| Discovery | | | | |

## Actions executed
| Keyword | Campaign | Change | Old bid | New bid | Reason |
|---------|----------|--------|---------|---------|--------|
| | | Bid +10% / Pause / New | | | |

## New keywords added
| Keyword | Match | Campaign | Starting bid |
|---------|-------|----------|--------------|
| | EXACT | Category | $ |

## Negatives (→ asa-negative-keywords)
- [N] terms flagged, estimated weekly savings: $___

## Scale recommendations
1. [action from admaxxing or ROAS analysis]
2. [action]

## Next week focus
- [specific campaign or keyword cluster to watch]

Common Mistakes

  • Changing bids daily — ASA needs 3–5 days to reflect bid impact
  • Pausing discovery before mining search terms — always pull search terms first
  • Scaling competitor campaigns with brand-level ROAS expectations
  • Ignoring TTR — low TTR means creative/metadata problem, not bid problem
  • Adding broad match keywords to brand campaign — keep match types clean per campaign

Cross-Skill Handoffs

SituationRoute to
Full ROAS deep diveasa-roas-analysis
Automated scale playbookasa-admaxxing
Block wasted termsasa-negative-keywords
Low CVR on good keywordsaso-skills custom-product-pages, ab-test-store-listing
New to ASA structureaso-skills apple-search-ads

Related Skills

  • asa-roas-analysis — profitability data driving decisions
  • asa-negative-keywords — block wasted search terms
  • asa-admaxxing — automated scale recommendations
  • aso-skills apple-search-ads — campaign structure and strategy
  • aso-skills keyword-research — seed keywords for new campaigns

Frequently asked questions

What does the Asa Weekly Optimization AI skill do?

When the user wants a weekly Apple Search Ads optimization routine — keyword bids, pauses, new opportunities, and budget pacing. Use when the user mentions "weekly ASA", "optimize Apple Search Ads", "ASA keywords", "ASA maintenance", or "ASA bid changes". For profitability analysis, see asa-roas-analysis. For automated scale playbook, see asa-admaxxing.

Why use Asa Weekly Optimization on TypingMind?

Because you install it once and use it with any model. Asa Weekly Optimization 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 Asa Weekly Optimization in TypingMind?

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

Which AI models can use Asa Weekly Optimization?

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 Asa Weekly Optimization?

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

Is the Asa Weekly Optimization 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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