The problem: At the end of the day, you need to explain what you did (standups, reports, timesheets). But tracking in real-time is exhausting and interrupts flow.

Anker flips this: *work first, summarize later*. It reconstructs your day from sources you already have: - Git commits (with full diffs) - Markdown notes - Obsidian vaults

Then generates summaries in multiple formats. The markdown format includes full git diffs, which makes it perfect for piping to AI:

```bash anker recap yesterday --format markdown | claude -p "Create standup notes" ```

I call this the *#AntiProductivity mindset* - focusing on meaning instead of metrics.

Built in Go, works locally (no cloud/tracking), MIT licensed. Took it from idea to v0.1.1 in about a week with Claude AI doing most of the heavy lifting.

Demo GIF in the README shows it analyzing HTB machine recon notes.

Would love feedback on: - What data sources would you want to track? - Is the "anti-productivity" messaging clear or confusing? - How would you use this in your workflow?