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Getting Started

Requirements

  • Bun runtime (>=1.0.0)
  • OpenCode CLI
  • AI agent supporting Agent Skills (OpenCodeAI, Claude Code, etc.)

Installation

Detailed installation instructions are available in the Installation guide.

Quick start:

bash
bun run install

This runs an interactive installer that lets you choose between:

  • Local - .opencode/ (current project only)
  • Global - ~/.config/opencode/ (all projects)
  • Custom - Specify any installation path

What Gets Installed

Every request goes through a structured execution flow:

  1. Classify Intent — What do you want?
  2. Load Context — Project rules for this task
  3. Load Skill — Appropriate specialist
  4. Execute — Do the work (follows Plan when applicable)
  5. Reflect — Revisit, rethink, re-evaluate

Plan Framework (when structured development needed):

  • PLAN — Define objectives and acceptance criteria (Given/When/Then)
  • APPLY — Execute with verification steps
  • UNIFY — Close loop, reconcile plan vs actual, update state

CARL Quality Gates (active throughout):

  • Dynamic rule loading based on domain
  • Priority-based enforcement (Critical > High > Medium)
  • Blocks on critical violations

Structure at the start, freedom at the end.

Running Scripts

AI Agent

The AI agent can run Tachikoma scripts directly as tools:

bash
tachikoma.where
tachikoma.edit-format-selector recommend

Manual

Use bun run for direct script execution:

bash
bun run .opencode/plugins/tachikoma/where.ts
bun run .opencode/plugins/tachikoma/edit-format-selector.ts recommend

Understanding Plan Methodology

Plan (Plan-Apply-Unify Loop) — Structured development framework for AI-assisted workflows.

  • PLAN — Define objectives and acceptance criteria (Given/When/Then format)
  • APPLY — Execute tasks sequentially with verification
  • UNIFY — Close loop, reconcile plan vs actual, update state

Never skip UNIFY — this is the heartbeat that prevents drift.

Quality over speed-for-speed's-sake. In-session context over subagent sprawl.

Learn more about Plan →

Understanding CARL

CARL (Context Augmentation & Reinforcement Layer) — Dynamic rule loading system.

CARL loads quality rules just-in-time based on context:

  • Context Detection — Detects active domains (Plan, Development, Projects)
  • Rule Loading — Loads relevant rules dynamically
  • Priority Enforcement — Critical blocks, high warns, medium notes

Three Domains:

  1. Plan Domain — Loop enforcement, boundary protection
  2. Development Domain — Code quality, error handling, testing
  3. Projects Domain — Documentation, version handling

Learn more about CARL →

Next Steps

Released under the MIT License.