jackwener

jackwener / AI-digest

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AI Agent Daily Digest — Collect and analyze your AI coding assistant usage

17
1
100% credibility
Found Mar 04, 2026 at 17 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A local tool that collects conversation logs from various AI coding assistants and generates structured daily activity summaries using a language model.

How It Works

1
🔍 Discover AI-Digest

You hear about a handy tool that gathers your daily chats with AI coding helpers and turns them into easy-to-read work summaries.

2
📥 Add to your computer

You quickly install the tool on your machine with a simple setup.

3
🔗 Link a smart helper

You share a private password with a thinking service so it can create clever reports.

4
📂 Gather your chats

You tell the tool to collect today's conversations from your AI coding sessions.

5
📊 See your day at a glance

A colorful timeline pops up, showing times, projects, and chat highlights from your day.

6
✨ Create the report

You ask it to summarize everything into structured highlights and activity details.

🎉 Enjoy your daily recap

You receive a clear, organized report of your work highlights and tasks, all in friendly Chinese.

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AI-Generated Review

What is AI-digest?

AI-digest is a Python CLI tool that pulls local logs from five AI coding agents—Claude Code, Codex, Antigravity, OpenCode, and Gemini CLI—to build a timeline of your daily sessions. Run `digest collect` for a Rich-formatted table of time, source, project, title, and message count; `digest analyze` sends it to your chosen OpenAI or Anthropic model for a structured Chinese report with highlights and detailed activities. It solves the hassle of manually tracking scattered AI agent usage across tools, delivering an agent daily report right in your terminal.

Why is it gaining traction?

Unlike scattered agent github claude or copilot logs, it aggregates everything locally with zero external deps for collection, handles local timezones, and spits out LLM-powered insights without fluff. Developers dig the config.yaml simplicity for any compatible API, plus pretty tables that beat digging through JSONL files—think agent daily club reviews, automated. Low stars (17) but hooks AI digest github fans chasing agent daily hive efficiency.

Who should use this?

Backend devs juggling Claude Code and Gemini CLI for agent github code reviews, or indie hackers on Codex/OpenCode needing agent daily salary breakdowns of AI time spent. Perfect for remote workers wanting agent daily worker customer service logs summarized, not frontend folks light on agents.

Verdict

Solid early experiment at 1.0% credibility and 17 stars—docs are crisp, MIT licensed, but lacks tests and broad agent support like Copilot IntelliJ. Grab it if you need agent daily caz reports now; watch for polish.

(178 words)

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