version: "1.0.0" name: performance-review description: How to run a performance review across ad accounts with Adako, the MCP server and REST API that connects this assistant to Google Ads, Meta Ads, ChatGPT Ads, TikTok Ads and LinkedIn Ads. Use it whenever the user asks how campaigns did, what a period cost and returned, why results changed, which campaigns are wasting money, how one week compares with the last, or asks for a weekly or monthly account review across one or several accounts. It gives the order of calls per platform, the metric each objective is judged on, how to fan out across accounts, how to explain a change instead of guessing at it, and how to present the numbers. license: MIT

Running a performance review

Adako is an MCP server and REST API that connects Claude, ChatGPT, Cursor and other assistants to Google Ads, Meta Ads, ChatGPT Ads, TikTok Ads and LinkedIn Ads. This skill is the reading half: how to answer "how are we doing" with numbers that hold up.

Reads run immediately, change nothing and are free. Every call in a review is a read, so none of them goes through a _write router.

Start

1. start_here if you do not know what is connected. Free.
2. list_connected_accounts for ids, names, currencies and timezones. Free.
3. Fix the window before calling anything. last_30_days by default; last_7_days only when the

user asked for the week, and then say a week is not a trend.

Every performance tool returns the previous period of the same length beside the current one. Report both. A number without its baseline is not an answer.

The first call per platform

Everything deeper goes through the platform's read router: google_ads(action="execute", tool_name="google_get_ad_group_performance", arguments={...}).

Judge each objective on its own metric

• Google Search: cost, clicks, CTR, conversions, CPA, and ROAS only where conversion value exists.
• Meta: the tool already picks the objective's KPI. Purchases and purchase ROAS for sales, leads and

cost per lead for lead generation, link clicks and CPC for traffic, reach and CPM for awareness.

• TikTok: spend, clicks, conversions, plus the video set. Hook rate (2-second views over

impressions), 6-second views, completion, average watch time.

• LinkedIn: spend, clicks, CTR, CPC, leads, cost per lead, website conversions. Engagement metrics

are a separate call, linkedin_get_engagement_metrics.

• ChatGPT Ads: impressions, clicks, spend, conversions and the derived ratios.

Do not report ROAS on an objective that records no revenue. Say what the account actually measures.

Narrowing down

Work down one level at a time, and stop when the answer is clear.

Google google_get_campaign_performance → google_get_ad_group_performance → google_get_keyword_performance → google_analyze_search_terms. Cut sideways with google_get_device_performance, google_get_geo_performance, google_get_hourly_performance.

Meta meta_get_campaign_performance → meta_get_adset_performance (with a breakdown) → meta_get_ad_performance. Then meta_optimize_placements and meta_analyze_audiences.

TikTok tiktok_get_campaign_performance → tiktok_get_ad_group_performance → tiktok_get_ad_performance, plus tiktok_get_audience_insights and tiktok_analyze_geo_performance.

LinkedIn linkedin_get_campaign_performance → linkedin_get_creative_performance, plus linkedin_get_audience_insights for job title, industry, seniority and company size.

Explaining a change

Never guess at a cause. Three tools decompose one:

• google_explain_performance_anomaly ranks campaigns, devices, networks, countries and search terms

by how much of the change each accounts for.

• meta_explain_anomaly attributes a change to ad sets, placements, countries or age and gender.
• Where no decomposition tool exists, compare the two periods at the next level down and say which

object moved.

If the data does not explain the change, say that, and name what would: a tracking gap, a seasonal week, a creative approved mid-period, a budget raised on the 14th.

Finding waste

• google_analyze_wasted_spend and google_analyze_search_terms
• meta_analyze_wasted_spend and meta_detect_creative_fatigue
• tiktok_analyze_wasted_spend and tiktok_detect_creative_fatigue
• linkedin_analyze_wasted_spend and linkedin_analyze_creative_performance

Each excludes the learning phase and trivial spend, so treat what they return as real. Present waste as money and share of spend, not as a list of ids.

Several accounts at once

A platform read router fans a read out across accounts:

google_ads(action="execute", tool_name="google_get_campaign_performance", arguments={"date_range":"last_30_days"}, accounts="all_active")

• accounts takes a list of ids or "all_active". Reads only, free, at most 20 accounts.
• One table per currency. Never sum or average across currencies.
• Name the accounts included, and say which were skipped and why.
• Check get_usage_status first on a small plan.

Presenting it

1. One sentence with the headline: spend, the objective's KPI, and the direction against the previous

period.

1. One table: campaign, spend, the KPI, the change. Numbers with currency, tabular and rounded

sensibly.

1. Two or three findings, each tied to a number you actually read.
2. One recommendation, with the tool that would carry it out and what it would cost. Do not run it.

Recommend a pause only after explaining what the money bought. Weak performance in a window is not proof of a bad campaign.

Do not

• Do not average metrics across accounts in different currencies.
• Do not present a 7-day window as a trend.
• Do not compute a metric the tool already returns; use its own numbers.
• Do not attribute a change to a cause you did not measure.
• Do not spend the user's whole quota fanning out when one account answers the question.