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FlorianBruniaux

gsc-mcp

page_analysis

Join Google Search Console and Google Analytics 4 data at the page level to rank pages by opportunity score, combining impressions, engagement rate, and conversions.

Instructions

Join GSC and GA4 data at the page level and rank by opportunity score.

GSC rows are fetched with dimensions=["page"] (already aggregated per page). GA4 organic landing pages are fetched with a high limit to avoid truncation. Pages are joined on _normalize_url. Pages that appear in only one source get None for the missing fields.

opportunity_score = log10(impressions+1)10 + engagement_rate100 + log10(conversions+1)*20

engagement_rate is derived as engaged_sessions/sessions (GA4 native formula) because ga4_organic_landing_pages does not expose it directly.

Results are sorted by opportunity_score descending, truncated to limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteYes
daysNo
limitNo
property_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description provides detailed behavioral disclosure: how GSC rows are fetched, GA4 landing pages are fetched, join logic, handling of missing fields, the scoring formula, sorting, and truncation. It does not cover permissions, rate limits, or error handling, but gives sufficient transparency for an analytical tool.

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

Conciseness4/5

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

The description is a single paragraph that front-loads the main purpose in the first sentence. It is concise and uses efficient language, but could benefit from bullet points or separation of key details for better readability.

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

Completeness4/5

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

Considering the tool's complexity (4 parameters, custom algorithm) and the presence of an output schema, the description is fairly complete. It explains the join logic, score derivation, sorting, and truncation. However, it lacks explanations for parameters and prerequisites, such as site configuration.

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

Parameters2/5

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

The input schema has 4 parameters with 0% description coverage. The description only mentions 'limit' implicitly. It does not explain the meaning or usage of 'site', 'days', or 'property_id', leaving the agent to infer from parameter names. This is insufficient for effective tool selection and invocation.

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 'joins GSC and GA4 data at the page level and ranks by opportunity score,' using specific verbs and resources. It differentiates from sibling tools like 'get_search_analytics' and 'ga4_organic_landing_pages' by combining both data sources and applying a custom scoring formula.

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 context on what the tool does (page-level analysis with custom scoring) but does not explicitly state when to use it versus alternatives or when not to use it. The context implies it is for ranking opportunities, which is distinct from other tools, but lacks explicit exclusions.

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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