mindwalk: see what your AI coding agent actually did, in 3D

2 months ago

Your coding agent just ran a session you can't read. Mindwalk plays it back as light on a three-D map of your code, and you watch exactly where it went.

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  1. 0:00Slide 1
  2. 0:07It draws your repo, then replays the run on it
  3. 0:23The log exists. Nobody can read it.
  4. 0:36Every file keeps its deepest touch
  5. 0:48Three pieces, kept deliberately apart
  6. 1:10Drive it like a video
  7. 1:25Optionally, the AI grades the AI
  8. 1:48Getting it is easy
  9. 2:05mindwalk
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Slide 1

GitHub Trending · Ep 08 · Jul 14, 2026
mindwalk: see what your AI coding agent actually did, in 3D
Replay your AI coding agent's session as light on a 3D map of your codebase
Go MIT macOS Linux Windows

Your coding agent just ran a session you can't read. Mindwalk plays it back as light on a three-D map of your code, and you watch exactly where it went.

It draws your repo, then replays the run on it

mindwalk's 3D night-map: the repository drawn as a radial tree on black, with glowing paths lit where the coding agent searched, read, and edited; everything untouched stays dark
Where the agent searched, read, and edited glows; everything else stays dark
The agent's grasp of the task becomes a shape you read at a glance

Point it at a session from Claude Code or Codex, and it draws your repo as a map, then replays the run on top. Wherever the agent searched, read, or edited, the map glows. Everything else stays dark. The agent's grasp of the task becomes a shape you read at a glance.

The log exists. Nobody can read it.

mindwalk terrain view: the repository as a treemap, files glowing by how deeply and how often the agent touched them
Raw JSONL never shows which parts of the repo the agent leaned on, or whether it stayed in scope
Mindwalk turns it into a picture you read in seconds

That log already exists, but it's raw JSONL. Reading it line by line never tells you which parts the agent leaned on, or whether it stayed in scope. Mindwalk turns it into a picture you read in seconds.

Every file keeps its deepest touch

seen moss green, only glanced at
read moon white, opened and read
edited warm amber, changed
unvisited dark, never opened
Review strip: error rate · churned files · edits after last verify

Every file keeps its deepest touch, color-coded. Green, the agent only glanced at it. White, it read it. Amber, it made edits. Still dark, it never opened it. And up top, a review strip pulls out the friction it found.

Three pieces, kept deliberately apart

trace your session, flattened into ordered file touches
→
citymap your repo's layout
→
report LLM-judge findings
local Go server · serves the React / Three.js frontend
citymap is deterministic: the same tree always draws the same map · maintainer's design claim
so two sessions over one repo line up in the same space · set them side by side and compare · a comparable replay, not just a prettier one

Under the hood, three pieces kept apart. The trace is your session, flattened into ordered file touches. The citymap is your repo's layout, and here's the clever bit, it's deterministic: the same tree always draws the same map. So two sessions over one repo line up in the same space, and you can set them side by side and compare. Not a prettier replay, a comparable one.

Drive it like a video

mindwalk playback deck: transport controls and a cool-to-warm histogram of the session, cool search and read bars on the left rising to a warm edit cluster mid-right, with an event legend
Cool bars = observing (search, read). Warm bars = mutating (edit, verify). Editing phases pop.
◇ compactions · ○ subagents · › turns · click to jump

You drive it like a video. Scrub or play the session over a histogram: cool bars are the agent looking around, warm bars are it editing, so the edits pop out. And every big event, context compactions, subagent launches, is a mark you can jump straight to.

Optionally, the AI grades the AI

The feature mindwalk analyze asks your local claude or codex to judge exploration, scope, wandering, and verification. Each finding is pinned to a timeline event.
The honest boundary Fully local. The one thing that ever leaves is that session's summary, sent to the model behind your account, and only when you run it. The judge runs sealed: no tools, no MCP, no persistence.

And it can grade the session. Optionally, mindwalk asks your own local claude or codex command line to judge how the agent worked, where it wandered, whether it verified. Now the honest part. Everything else is fully local. This one step is the exception: when you run it, and only then, a summary of that session goes to the model behind your own account. Nothing leaves while you're just viewing.

Getting it is easy

install curl -fsSL .../install.sh | sh → ~/.local/bin, checksum-verified
source make setup && make build
run mindwalk with no args scans Claude Code + Codex, serves the UI, opens your browser
MIT v0.1.0 Go binary macOS · Linux · Windows
github.com/cosmtrek/mindwalk

Getting it is easy. A curl script drops a single Go binary into your local bin, or you build from source with make. Then run mindwalk with no arguments, and it finds your Claude Code and Codex sessions, serves the UI locally, and opens your browser. MIT, version zero point one, macOS, Linux, and Windows.

mindwalk

See what your coding agent actually did, in 3D
github.com/cosmtrek/mindwalk
Worth a star and a weekend.
New repo tomorrow.

So, mindwalk. It's brand-new, version zero point one, from cosmtrek, the developer behind air. Not battle-tested yet. But if you run a coding agent every day, this is a genuinely new way to see what it actually did. Worth a star and a weekend. The link's on screen, and there's a new repo tomorrow.