relevance-analytics

Query Relevance AI agent analytics by project, agent, or date range.

1|Updated Mar 12, 2026
One-click install
npx skills add https://github.com/RelevanceAI/agent-skills --skill relevance-analytics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: relevance-analytics
Source: https://github.com/RelevanceAI/agent-skills/tree/main/reference/relevance-analytics
Command: npx skills add https://github.com/RelevanceAI/agent-skills --skill relevance-analytics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Retrieves usage analytics for Relevance AI agents and projects, enabling teams to understand adoption, performance, and workload distribution.

Core Features & Use Cases

  • Retrieve agent analytics, including most active agents and execution counts.
  • Analyze usage trends over time and identify idle or underutilized agents.
  • API-driven approach to fetch analytics for both agents and projects for planning and optimization.

Quick Start

Ask the AI to run a query for /agents/analytics with filters to return recent agent activity, then review the resulting timeseries and totals.

Frequently Asked Questions about relevance-analytics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I retrieve agent usage analytics for my Relevance AI projects?▼

You retrieve agent usage analytics by querying the /agents/analytics endpoint with project, agent, or date range filters. The API returns a structured payload containing timeseries, total_change, and last_updated_at results for your agents.

What metrics are included in agent analytics timeseries data?▼

Agent analytics timeseries data includes usage patterns, activity metrics, execution counts, and total_change values. The structured payload also provides last_updated_at timestamps to help track agent adoption and workload distribution over time.

Can I filter agent analytics by specific projects or date ranges?▼

You can filter agent analytics by project, agent, or date range when querying the /agents/analytics endpoint. This allows you to isolate specific usage trends, identify idle agents, and monitor execution counts across targeted time periods.

How do I identify underutilized or idle agents using analytics?▼

You identify underutilized agents by analyzing usage trends and execution counts from the analytics timeseries data. Querying /agents/analytics with date range filters reveals activity metrics and total_change values to pinpoint agents with low or no recent activity.

What is the best way to monitor agent execution counts over time?▼

The best way to monitor agent execution counts is by querying the /agents/analytics endpoint to retrieve timeseries data. This API-driven approach returns structured activity metrics and total_change values for tracking agent usage trends and planning optimization.

Does this analytics approach require any external dependencies?▼

This analytics approach requires no external dependencies. It uses the relevance_api_request to call POST /agents/analytics directly, returning structured timeseries and total_change data without needing additional setup or external libraries.