DEDUPED Hot AI repos, turned into use cases Get 5 a day

How to measure your AI coding usage across tools and projects with AI Data Extractor

Count sessions, projects, and models over time from your extracted assistant conversations.

Who it is forA developer or team lead who wants to see how they use different AI coding assistants across projects.

The problemUsage is split across several tools with different storage formats, so there is no single view of it.

The outcomeA summary table of sessions per source, project, model, and month, built from the normalized JSONL files.

What you need first

  • Python 3.9 or newer installed on the machine that holds the chat history
  • The AI coding tools installed under your own user account, with local chat history present
  • Permission to read and store your own local data, and a secure place to keep the output
  • For the fine-tuning case: the Hugging Face datasets library and a tokenizer for your target model

Steps

  1. Run python extract.py --all --merge to write all_conversations.jsonl with every found source.
  2. Write a short Python script using the standard library to read all_conversations.jsonl one line at a time. (inferred, check the README)
  3. Group records by the source, project_path, and timestamp fields, counting sessions by session_id. (inferred, check the README)
  4. Print the counts per source and per month, and save them to a CSV file. (inferred, check the README)

Prompt for your agent

Using the repo jatechan/ai-data-extractor, read extracted_data/all_conversations.jsonl from <project folder> and count unique session_id values grouped by source and by month of the timestamp. Output a CSV table with those counts. Verify that the total of session counts equals the number of unique session_id values in the file.

Caveat. Fields vary by source, so some tools will not record model names, project paths, or timestamps, and those rows will be missing from the counts.

Share: X LinkedIn Hacker News Email Copy link

Disclaimer

Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked "Seen in the wild", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email [email protected] and we will look at it promptly. Full disclaimer page