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google_ads_creative_research

Draft or refresh Google Ads creative by collecting all necessary inputs: landing page analysis, top-performing ads, search term insights, keyword suggestions, and existing keywords.

Instructions

Collect every input an LLM needs to draft or refresh Google Ads creative for a single campaign. Returns {campaign_id, url, lp_analysis (same shape as google_ads_landing_page_analyze), existing_ads:[{ad_id, headlines, descriptions, final_urls, impressions, clicks, conversions, ctr}] (top 5 RSA ads by impressions, REMOVED excluded), search_term_insights:{high_cv_terms (top 10 by conversions), high_click_terms (top 10 by clicks), total_terms}, keyword_suggestions (KeywordPlanIdeaService output for up to 5 seeds derived from LP title + h1 + meta_description), existing_keywords (list_keywords output), context_summary (string)}. Any failing sub-step is replaced with the literal string '取得失敗' so the envelope never raises. Side effect: one outbound LP fetch (same SSRF policy as google_ads_landing_page_analyze) plus several GAQL queries. For just the LP use google_ads_landing_page_analyze; for just RSA asset diagnostics use google_ads_rsa_assets_analyze.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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.
campaign_idYesCampaign ID as a numeric string without dashes (e.g. '23743184133'). Obtain via google_ads_campaigns_list.
urlYesAbsolute landing page URL to analyze (http:// or https:// only, e.g. 'https://example.com/lp/'). SSRF-protected — private-range, loopback, and cloud-metadata hosts are rejected.
ad_group_idNoOptional ad group ID as a numeric string (e.g. '145680123456') to restrict results to a single ad group. Omit to include every ad group matching the campaign filter.
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses side effects (one outbound LP fetch, several GAQL queries) and error handling (failing sub-steps replaced with '取得失敗' to avoid exceptions). It could have explicitly stated read-only nature but is otherwise transparent.

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 a single dense paragraph that front-loads the purpose, details the return structure, error handling, side effects, and usage alternatives. Every sentence adds value, with no wasted words.

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 tool's complexity (aggregating data from multiple sub-tools) and the absence of an output schema, the description provides a complete breakdown of the return object, including field shapes, limits (top 5 ads, top 10 terms), and references to other tools. It covers error behavior and side effects fully.

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

Parameters3/5

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

The input schema already has 100% description coverage for all 4 parameters. The description adds value by explaining the overall context and output structure but does not enhance parameter meanings beyond the schema. Baseline 3 applies.

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 the tool collects all inputs needed for an LLM to draft or refresh Google Ads creative for a single campaign. It specifies the return object structure and distinguishes from sibling tools like google_ads_landing_page_analyze and google_ads_rsa_assets_analyze.

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 (for full creative research) and when not to: 'For just the LP use google_ads_landing_page_analyze; for just RSA asset diagnostics use google_ads_rsa_assets_analyze.' This provides clear guidance on alternatives.

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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