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Python
Hybrid

google_ads_auction_insights_analyze

Interprets impression-share metrics for a Google Ads campaign and surfaces actionable insights when share is low, rank or budget loss exceeds 20%, or absolute top impression share is under 20%.

Instructions

Interpret a campaign's impression-share metrics and surface human-readable insights about competitive position. Returns {campaign_id, campaign_name, period, impression_share_metrics:{search_impression_share, search_rank_lost_is, search_budget_lost_is, search_top_is, search_abs_top_is, note}, insights:[strings], note}. Each impression-share value is a percentage (0-100, rounded to 1 decimal) or None. Insights fire when IS < 50/70%, rank-lost > 20%, budget-lost > 20%, or abs-top-IS < 20%. Read-only. Note: Google Ads API v23 removed competitor-level auction_insight (domain overlap, outranking share); only impression-share proxies are returned. For the raw metrics without insights use google_ads_auction_insights_get; full competitor data is only available in the Google Ads UI.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoReporting window for the metrics. Default 'LAST_30_DAYS'. Use a shorter window (LAST_7_DAYS / LAST_14_DAYS) when diagnosing recent changes; use LAST_90_DAYS for trend baselines.
campaign_idYesCampaign ID as a numeric string without dashes (e.g. '23743184133'). Obtain via google_ads_campaigns_list.
customer_idNoGoogle Ads customer ID as a 10-digit string without dashes (e.g. '1234567890'). Optional — falls back to GOOGLE_ADS_CUSTOMER_ID / GOOGLE_ADS_LOGIN_CUSTOMER_ID from the configured credentials when omitted.

Tool Definition Quality

A5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses behavior beyond annotations, which are absent. It explains that it is read-only, lists the exact metrics returned, notes the removal of competitor data in API v23, and details insight thresholds. This fully compensates for lack of annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise at 5 sentences, front-loaded with the main purpose, and structured logically. Every sentence provides unique value, with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema, the description adequately explains the return shape, including the structure of impression_share_metrics and insights array. It also provides necessary context about API limitations, making it complete for the agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description adds extra meaning: for 'period', it suggests usage scenarios (shorter windows for diagnosis, longer for baselines); for 'customer_id', it explains fallback credentials; for 'campaign_id', it references how to obtain it. This surpasses schema info.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it interprets impression-share metrics and surfaces human-readable insights. It distinguishes itself from the sibling tool 'google_ads_auction_insights_get' by specifying that this tool adds insights, while the sibling returns raw metrics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when to use this tool vs alternatives: it notes that for raw metrics, use 'google_ads_auction_insights_get', and that competitor-level data is only in the UI. It also explains the conditions under which insights fire, aiding decision-making.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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