Agents ship the code. HQFlow shows you the system.

Agents ship faster than you can reread the repo. HQFlow maps what they built, entry point to failure path.

$npx hqflow init
$npx hqflow open

Reading isn't enough.

In an AI-native codebase the scarce resource isn't generation. It's keeping the architecture in view after every feature ships.

Read the code

Agents ship features faster than you can re-absorb the architecture.

Read the docs

Walls of markdown and HTML. Accurate maybe, but no shape.

See the system

A sourced map of real workflows: entry, decisions, side effects, outputs.

One loop, three moves.

Your agent writes. HQFlow validates and draws. You read the result and ask for the next workflow.

Scaffold

hqflow init drops a .codehq/ into your repo: a strict JSON contract and a SKILL.md your agent already knows how to read.

.codehq/
├── project.json
├── SKILL.md          agent contract
├── diagnostics.json  repair loop
└── workflows/

Author

Your agent traces real code paths and writes workflow JSON: steps, sources, edge cases, tests. Every claim marked verified or inferred.

{
  "id": "check-quota",
  "category": "decision",
  "confidence": "verified",
  "sources": [{ "file": "lib/validation.ts",
               "symbol": "hasRemainingQuota" }]
}

Observe

HQFlow validates every file, watches for changes, and re-renders the canvas live. Invalid files become precise diagnostics, never a blank board.

issues[0]: error
  connections[3].to  step "send-receipt"
  does not exist.
  hint: point to an existing step id.

The system, drawn honestly.

Every node is a real step backed by real files. Colour is meaning. Dashes are doubt. Click a step to see what it touches, what can break, and the tests that prove it.

HQFlow motiona / generate-video watching local files
click a step to inspect it
7 steps · 9 connections · 3 passing tests

Rendered from examples/motiona/.codehq/workflows/generate-video.json

An instrument, not a chatbot.

Local-first

Renders from files on disk. No accounts, no telemetry, no runtime network calls beyond localhost. Your code never leaves the machine.

No LLM inside

HQFlow contains no model and no prompts. Your agent is the brain. HQFlow is the instrument that keeps it honest.

Agent-proof schema

Strict Zod schemas reject invented fields, especially visual ones. Layout, colour and typography are computed by HQFlow, never authored by a model.

Last-valid-state

A half-written file never blanks the board. The last valid map stays on screen while diagnostics guide the repair.

Point it at a repository.

$npx hqflow initscaffold .codehq/
$npx hqflow openstart the local canvas
$npx hqflow validatecheck what your agent wrote

then ask your agent

“Map how checkout actually works in this repo: steps, sources, failure paths. I’ll review the architecture on the canvas.”

Works with Cursor, Claude Code and Codex. Anything that can read a repo.