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FlorianBruniaux

gsc-mcp

traffic_health_check

Compare total Google Search Console clicks with total Google Analytics 4 organic sessions to detect tracking gaps, filter issues, or healthy traffic.

Instructions

Compare total GSC clicks with total GA4 organic sessions to detect tracking gaps.

Fetches aggregate GSC clicks (no page dimension) and sums all organic sessions from GA4. The ratio ga4_sessions / gsc_clicks indicates tracking health:

  • "no_gsc_data" : zero GSC clicks (ratio is None, nothing to compare)

  • "tracking_gap" : ratio < 0.6 (GA4 records far fewer sessions than GSC clicks)

  • "filter_issue" : ratio > 1.3 (GA4 records more sessions than GSC clicks)

  • "healthy" : 0.6 <= ratio <= 1.3

Boundaries 0.6 and 1.3 are inclusive of the healthy range (strict < and >). GA4 is queried with limit=10000 to avoid under-counting sessions on large sites. hostname and country narrow the GA4 query to a specific host or country.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
siteYes
countryNo
hostnameNo
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 handles transparency well: it details the ratio calculation, the four outcome categories with their thresholds (including inclusivity), and mentions the GA4 query limit of 10000 to avoid undercounting. It also notes that hostname and country narrow the query. This gives a clear behavioral model, though it could mention error handling or rate limits.

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 well-structured: it starts with a clear purpose, then explains the ratio and outcomes with examples. While slightly long, each sentence adds necessary information. The bullet list of outcomes is clear but could be condensed slightly.

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?

Given the tool's complexity, the description covers the main behavior: the comparison, ratio interpretation, threshold boundaries, and query limit. With the presence of an output schema (context signal), the description's inclusion of outcome categories makes it largely complete. Minor gaps like handling of missing GA4 data or zero sessions are not addressed.

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 has 5 parameters with 0% description coverage. The description adds meaning for 'hostname' and 'country' (they narrow the GA4 query) and implies a default 'days' of 28 (via schema default), but it does not explain 'site' or 'property_id'. It partially compensates for the low schema coverage but not fully.

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 compares total GSC clicks with total GA4 organic sessions to detect tracking gaps. It uses a specific verb and resource, and the unique function distinguishes it from sibling tools like analytics_anomalies or ga4_traffic_sources.

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

Usage Guidelines3/5

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

The description implies the tool should be used to detect tracking discrepancies between GSC and GA4, but it does not explicitly state when to use or when not to use it, nor does it compare to alternatives. The guidance is adequate but lacks explicit recommendations.

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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