Diagnose GTM performance gaps from cross-skill data outputs.
npx skills add https://github.com/sahin/claude-skills --skill gtm-analytics-sahin
Please help me install this Agent Skill. Skill: gtm-analytics Source: https://github.com/sahin/claude-skills/tree/main/gtm-analytics Command: npx skills add https://github.com/sahin/claude-skills --skill gtm-analytics-sahin
This Skill provides cross-skill GTM visibility by ingesting outputs from multiple GTM sources to diagnose performance bottlenecks, misalignments, and opportunities, translating raw data into an actionable diagnostic report instead of just dashboards.
Run GTM analytics on the current data/gtm set to generate a diagnostic report.
High-intent search queries and answers about installing and using this skill.
Diagnosing GTM performance bottlenecks requires correlating funnel stages, channel attribution, and cohort trends. Cross-skill analytics ingests outputs from multiple GTM data sources to identify root causes and translate raw data into an actionable diagnostic report.
Yes, you can analyze partial GTM data. The analytics process performs a data inventory to detect existing files and missing data, adapting the analysis to available information while highlighting data quality gaps and recommending skills to run next.
Identifying channel attribution and content performance gaps is best achieved through cross-skill diagnostics. This approach correlates channel performance and content impact with funnel stages to pinpoint root causes and prioritize actionable fixes.
Generate a diagnostic report by running GTM analytics on your current data set. The system reads outputs from all GTM skills, performs a data health check, and produces a prioritized diagnostic with concrete next steps and a recommended skill sequence.
No, specific GTM data files are not strictly required beforehand. A data inventory and health check detects which files exist and which are missing, adapting the analysis to available data while recommending skills to close any data gaps.
Your GTM analytics report shows partial trends because of missing data sources. A data health check detects these quality gaps, adapts the cross-skill diagnostics to available information, and provides a recommended skill sequence to close the gaps.
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