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kenlim5656

paid-media-mcp

by kenlim5656

get_keyword_performance

Retrieve keyword performance data including spend, quality scores, and impression share metrics. Use low_quality_score and lost_is_budget flags to identify optimization opportunities.

Instructions

Keyword performance with spend, quality scores, and Google impression share metrics. Excludes negative keywords. Returns quality_score (1–10), avg_search_impression_share, avg_IS_lost_budget, and avg_IS_lost_rank. Use low_quality_score=true to find SQO opportunities and lost_is_budget=true to find keywords throttled by budget caps. Requires BigQuery mode.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
platformNo
min_spendNo
campaign_idNo
lost_is_budgetNo
low_quality_scoreNo
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 the prerequisite (BigQuery mode) and excludes negative keywords. It lists returned metrics but does not mention whether the operation is read-only, permissions required, or any side effects.

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 two sentences, each serving a distinct purpose: first defines the tool's core output, second details actionable filters. No redundant information; every sentence adds value.

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

Completeness3/5

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

With no output schema or annotations, the description covers return metrics and two filter parameters. However, it omits explanations for three parameters (platform, min_spend, campaign_id) and does not describe output structure, pagination, or data limits, leaving gaps for a tool with this complexity.

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?

Schema coverage is 0%, and the description explains two of five parameters (low_quality_score and lost_is_budget) with purpose and usage examples. The remaining three parameters (platform, min_spend, campaign_id) are left unexplained, requiring the agent to infer their meaning from names.

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 explicitly states the tool returns 'keyword performance with spend, quality scores, and Google impression share metrics', specifying the metrics and excluding negative keywords. It clearly distinguishes from sibling tools like get_campaign_performance or get_ad_performance by focusing on keyword-level data.

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

Usage Guidelines4/5

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

The description provides clear usage guidance for optional filters: low_quality_score for SQO opportunities and lost_is_budget for budget-throttled keywords. However, it does not mention when not to use this tool or suggest alternatives for broader filtering.

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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