skills-summarizer

Summarize skill usage logs into JSON and HTML reports.

4|1|Updated Jan 13, 2026

Search Tags:#automation #summarization #skills #reporting #log analysis #telemetry

Ready to run

npx skills add https://github.com/rm2thaddeus/Aitor_Skills --skill skills-summarizer

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: skills-summarizer
Source: https://github.com/rm2thaddeus/Aitor_Skills/tree/main/skills-summarizer
Command: npx skills add https://github.com/rm2thaddeus/Aitor_Skills --skill skills-summarizer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill automates the process of summarizing skill usage logs, generating upkeep reports, and proposing conservative improvements to skills, reducing manual analysis time and effort.

Core Features & Use Cases

Log Summarization: Processes raw skill usage logs (.jsonl) into human-readable JSON and HTML reports.
Upkeep Reporting: Identifies key metrics like total invocations, unique skills used, and top projects.
Improvement Proposals: Suggests low-risk, high-impact skill enhancements based on usage data.
Use Case: After a week of agent activity, use this skill to generate a summary report detailing which skills were used most, by which projects, and to identify any skills that haven't been used and might be candidates for deprecation.

Quick Start

Run the skills summarizer script to generate upkeep reports for the last 7 days.

Frequently Asked Questions about skills-summarizer

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

FAQPage Schema

How do I summarize skill usage logs into readable reports?▼

To summarize skill usage logs, run the provided Python scripts to parse raw .jsonl telemetry files and output human-readable JSON and HTML reports. This process identifies usage patterns and total invocations across projects.

What is agent telemetry analysis for skill maintenance?▼

Agent telemetry analysis monitors skill performance by parsing usage logs to identify top projects, total invocations, and unused skills. It generates upkeep reports to help maintain and propose conservative improvements to your skill catalog.

Can I use Python scripts to parse .jsonl files for skill improvements?▼

Yes, you can use Python scripts to parse .jsonl log files and catalog skill metadata. The scripts process telemetry data to identify usage patterns and propose low-risk, high-impact skill enhancements.

What's the best way to identify unused skills for deprecation?▼

The best way to identify unused skills is to generate an upkeep report from your agent telemetry logs. The report highlights skills with zero invocations over a specified period, making them clear candidates for deprecation.

Do I need Python to generate HTML reports from agent telemetry?▼

Yes, you need Python to run the scripts that parse raw skill usage logs and generate both JSON and HTML upkeep reports. The scripts require no external dependencies to process your telemetry data.

What limitations exist when proposing improvements from log analysis?▼

The log analysis proposes only conservative, low-risk skill improvements based on usage data. It does not execute changes automatically but rather suggests enhancements by identifying usage patterns and cataloging skill metadata from telemetry logs.