Kanban CLI: A Local-First, Agent-First Task Manager for the Terminal

Kanban CLI is a local-first, agent-first terminal-based project management tool written in Rust. It brings structured agile workflows to the command line, with deep git integration designed to tame the randomness of AI coding agents.
Workflow: Skills, Isolation, Review
The tool defines a 4-step workflow for agent-driven development:
- The model reads a skill to contextualize requirements.
- It authenticates and receives a strict, schema-validated JSON payload outlining exact files, context, and acceptance criteria.
- Implementation runs inside an automatically isolated Git worktree and branch. The tool tracks progress (e.g., verifying all files edited) before submission.
- A human reviewer evaluates the submission and manually transitions the task to “Done,” triggering the final merge and cleanup.
Key Features
- Rust-based – compiled binary, no runtime dependency.
- Git integration – automatic branch/worktree isolation per task.
- JSON schema validation – enforces required fileds in agent output.
- Role Pool system – built-in roles with claim workflow.
- Sprint lifecycle – scope creep detection, velocity tracking.
- Statistics engine – tracked metrics with recalibration support.
- Local-first storage – JSON-backed, atomic writes, file locking.
Project Structure
The repository is organized with clear documentation:
README.md– acts as an index to all documentation files.Concept docs– tasks, sprints, roles, statistics.Architecture docs– layered design, data model, concurrency.Reference docs– CLI commands, JSON output format, role pool.Development docs– Rust conventions, coding style.
Getting Started
Install via Nix or Cargo (see documentation for details). Initialize a project, create a task, assign a role, claim, and complete. All operations are local-first — no server needed.
The tool targets developers who want to enforce rigorous guardrails on agent-driven development while keeping full control in the terminal.
📖 Read the full source: HN AI Agents
👀 See Also

GoStaff: Go Rewrite of OpenClaw with 100x Memory Reduction
GoStaff is a Go rewrite of OpenClaw that uses approximately 100x less memory (~17MB) while maintaining OpenClaw plugin compatibility through a JavaScript shim. It features a three-tier skill system, unified Postgres persistence, and multi-provider ReAct loops.

EvalShift: Open-source CLI for detecting LLM regressions during model migration
EvalShift is an MIT-licensed Python CLI that compares source vs target LLM outputs across prompts, agents, and tool-calling workflows, generating a local HTML regression report.

ClawPy: Minimal Single-File Python Implementation of OpenClaw with Experience Memory
A developer built ClawPy, a stripped-down Python script that implements OpenClaw's autonomous task execution mechanics with a persistent experience system that learns from past errors and successes.

T9OS: An AI Orchestration System Built Entirely with Claude Code
An economics student built T9OS, a complete AI orchestration layer using Claude Code as the only programming tool. The system includes 18 production pipelines, a 12-state lifecycle engine, and 7 AI 'Guardians' that review every output.