skills.rest
kagenti
kagentiOFFICIAL
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session:extract

Extracts Cloud Code session analytics from GitHub comments into CSV, Markdown, or HTML files.

292|103|Updated Mar 27, 2025
Search Tags:#data extraction#markdown#html#github#reporting#csv#session analytics
One-click install
npx skills add https://github.com/kagenti/kagenti --skill session-extract
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: session:extract
Source: https://github.com/kagenti/kagenti/tree/main/.claude/skills/session%3Aextract
Command: npx skills add https://github.com/kagenti/kagenti --skill session-extract

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of extracting valuable session analytics from GitHub comments, making it easier to analyze and report on agent performance.

Core Features & Use Cases

  • Automated Data Collection: Fetches session comments from GitHub PRs and issues within a specified date range.
  • Metric Parsing: Extracts key session metrics from the comment content.
  • Report Generation: Outputs data into versatile formats: CSV for raw data, Markdown for reports, and HTML for interactive dashboards.
  • Use Case: A project manager can use this skill to generate a weekly report summarizing the performance metrics of AI agents based on their interactions logged in GitHub comments.

Quick Start

Run the extract phase to gather session analytics for the kagenti/kagenti repository, saving the output to /tmp/kagenti/session/.

Frequently Asked Questions about session:extract

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

FAQPage Schema
How do I extract session analytics from GitHub PR and issue comments into a report?▼

Extract session analytics from GitHub PR and issue comments by fetching comment data within a specified date range, parsing key metrics, and generating reports in CSV, Markdown, or HTML formats. The process utilizes Python scripts for data fetching and file generation.

Can I filter GitHub session data extraction by a specific date range?▼

Yes, you can filter GitHub session data extraction by a specific date range. The extraction process supports date range filtering to ensure you only collect and report on session analytics from your desired timeframe.

What formats can I export GitHub session analytics into for performance reporting?▼

You can export GitHub session analytics into CSV, Markdown, or HTML formats. CSV provides raw data for further analysis, Markdown suits text-based reports, and HTML enables interactive dashboard creation.

Do I need Python to generate CSV or Markdown reports from GitHub session comments?▼

Yes, you need Python3 installed to generate CSV or Markdown reports from GitHub session comments. The Skill utilizes Python scripts for fetching data, parsing session metrics, and generating the output files.

How does automatic repository detection work when extracting session analytics?▼

Automatic repository detection identifies the target repository context during data extraction, streamlining the collection of session analytics from GitHub PR and issue comments without requiring manual repository URL inputs.

What is the best way to summarize AI agent performance metrics logged in GitHub comments?▼

The best way to summarize AI agent performance metrics logged in GitHub comments is to automate data collection and metric parsing. This approach fetches session data within a date range and outputs structured CSV, Markdown, or HTML performance reports.

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