Google ads bidding

Skill kastriasani/google-ads-skills/skills/google-ads-bidding

13 Claude Code Agent Skills for Google Ads (research, planning, build, optimization, reporting) with a premium visual dashboard and a live example per skill.

Install

npx -y skills add kastriasani/google-ads-skills --skill google-ads-bidding

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What its author says it does

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Recommend the right Google Ads Smart Bidding strategy and target with guardrails, and allocate budget across campaigns for the best return. Use this whenever someone asks which bid strategy to use, whether to switch to Target CPA or Target ROAS, how to set a tCPA or tROAS target, whether to use Maximize Conversions or Maximize Conversion Value, how to move off Manual CPC, why a Smart Bidding campaign is underperforming or stuck in learning, how to set bid adjustments or device/location/schedule modifiers, or how to split a budget across campaigns to maximize conversions or value. Triggers include bid strategy, Smart Bidding, automated bidding, tCPA, tROAS, target CPA, target ROAS, Maximize Conversions, Maximize Conversion Value, Manual CPC, bid adjustment, bid modifier, budget allocation, and learning period. Runs standalone on pasted numbers; optional Google Ads API and GA4 sharpen it.

SKILL.md

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Google Ads Bidding

Pick the bid strategy and target that match the data the account actually has, set the right number, and attach the guardrails that stop common, expensive mistakes - tROAS with no value tracking, tCPA on five conversions a month, Broad match on Manual CPC. Then split the budget across campaigns toward the best return.

When to use

Reach for this skill when the user wants to:

Choose or change a bid strategy (Manual CPC, Maximize Clicks, Maximize Conversions, Target CPA, Maximize Conversion Value, Target ROAS).
Decide whether they have enough data to move to tCPA or tROAS, and what target to set.
Diagnose a Smart Bidding campaign that is underperforming or stuck in learning.
Set or rationalise bid adjustments (device, location, schedule, audience).
Allocate a fixed budget across campaigns to maximise conversions or value.

If the request is to forecast results or size a budget, use google-ads-forecast. If it is to design an experiment to test a bid change, use google-ads-ab-testing.

Workflow

Establish the data you have. You need: conversions in the trailing 30 days, whether conversion value is tracked, the goal (CPA or ROAS), the gross margin, and account/campaign maturity. These determine which strategies can even learn.
Get the recommendation. Run scripts/bid_strategy_advisor.py --conversions-30d 90 --value-tracking yes --goal roas --roas-target 5 --margin 30 --maturity established (or --demo). It returns the recommended strategy, the exact target to set, the rationale, the break-even ROAS, and hard guardrails. It enforces the thresholds: ~30 conversions/30d for Target CPA, ~50 plus value tracking for Target ROAS, and refuses to recommend tROAS without value tracking. See references/bid-strategies.md for the full progression and per-strategy detail.
Sanity-check the target against economics. Run scripts/roas_calculator.py to confirm break-even ROAS (100 / margin) and current CPA/ROAS, so any tCPA or tROAS you set clears break-even and ideally sits at 1.5-2x it to fund growth.
Allocate the budget. When several campaigns compete for one budget, run scripts/budget_mix_optimizer.py --input mix.json (or --demo). It scores each campaign on ROAS and effective (LTV-adjusted) ROAS, recommends a split under hard constraints (a floor on brand/defensive spend, a ceiling on concentration), and runs sensitivity scenarios (CPCs up, non-brand CVR down, learning under-delivery).
Handle bid adjustments correctly. Most percentage modifiers are ignored under Smart Bidding - the algorithm bids per auction. Use references/bid-adjustments.md to know what still applies (notably -100% exclusions and audience Observation signals) and avoid wasting effort tuning inert modifiers.
Deliver with guardrails. State the strategy, the target value, why, and the guardrails: do not pair Broad match with Manual CPC; expect a 1-2 week learning period after any switch or 20%+ target change; move targets 10-20% at a time; reallocate budget gradually so campaigns do not re-enter learning.

Inputs and data sources

Runs standalone: paste the numbers or hand the scripts a small JSON. Each script has a --demo mode and a --json flag for piping output into a report or sheet.

Optional sources that improve accuracy:

Google Ads API / UI - conversions/30d, current CPA and ROAS, bid strategy and status, learning-period state, per-campaign spend and value.
GA4 - conversion-value accuracy, assisted conversions, and offline-conversion imports so Smart Bidding optimises to revenue, not raw leads.
Google Sheets / BigQuery - hold campaign inputs and pipe --json output into a budget-allocation model.

Outputs

A recommended bid strategy with the exact target to set and the rationale.
Hard guardrails (data thresholds, things not to combine, learning-period rules).
Break-even ROAS and a target-sanity check against margin.
A constrained budget split across campaigns with sensitivity scenarios.
Correct, strategy-aware bid-adjustment guidance.

References

references/bid-strategies.md - each strategy: when to use it, the data it requires, and how to set its target, plus the full progression.
references/bid-adjustments.md - device/location/schedule/audience modifiers and how Smart Bidding overrides or honours each.