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Gentle-AI

Gentle-AI — Ecosystem, Frameworks, Workflows for AI coding agents.

Release License: MIT Go 1.25.10+ Platform


What It Does

Gentle-AI is NOT an AI agent installer. Most agents are easy to install. It is an ecosystem configurator that equips the AI coding agent(s) you already use with persistent memory, Spec-Driven Development (SDD), curated skills, MCP servers, model routing, a teaching-oriented persona, and bounded native review.

Before: "I installed Claude Code / OpenCode / Cursor, but it's just a chatbot that writes code."

After: Your agent now has memory, skills, workflow, MCP tools, and a persona that actually teaches you.

Supported Agent Integrations

Agent Delegation Model Key Feature
Claude Code Full (Task tool) Sub-agents, output styles
OpenCode Full (multi-mode overlay) Per-phase model routing
Kilo Code Full (multi-mode overlay) OpenCode-compatible config in ~/.config/kilo
Gemini CLI Full (experimental) Custom agents in ~/.gemini/agents/
Cursor Full (native subagents) 10 SDD agents in ~/.cursor/agents/
VS Code Copilot Full (runSubagent) Parallel execution
Codex Solo-agent CLI-native, TOML config
Windsurf Solo-agent Plan Mode, Code Mode, native workflows
Antigravity Solo-agent + Mission Control Built-in Browser/Terminal sub-agents
Kimi Code Full (native custom agents) Modular prompt templates in ~/.kimi
Kiro IDE Full (native subagents) Native ~/.kiro/agents/ + steering orchestration
Qwen Code Full (native sub-agents) Slash commands, ~/.qwen/commands/, auto_edit mode
OpenClaw Solo-agent Workspace-first AGENTS.md / SOUL.md with global MCP config
Trae Solo-agent Desktop app by ByteDance; ~/.trae/skills/ + OS-specific rules
Pi Full (package-managed subagents) First-class gentle-pi harness with Pi-native persona/models, SDD, and Engram memory
Hermes Detect-only YAML MCP config, SOUL.md persona; install manually first

Pi is package-managed, not just configured. Selecting Pi installs the first-class gentle-pi harness, which owns Pi-native persona and model controls, SDD assets, chains, and memory wiring.

Note: This project supersedes Agent Teams Lite (now archived). Everything ATL provided is included here with better installation, automatic updates, and persistent memory.

Delegation and Review Boundaries

Gentle-AI's workflow guidance keeps the parent/orchestrator thread thin. Once a task stops being small, delegation or an explicit SDD phase boundary is expected rather than optional.

Trigger Expected behavior
Reading 4+ files to understand a flow Delegate exploration or run an exploration phase.
Touching 2+ non-trivial files Use one focused writer and validate the result.
Implementation ready for review Start one bounded native review that freezes the candidate and creates a content-bound receipt.
Commit, push, or PR Validate that same receipt against the live Git candidate; never silently reopen review or create a new budget.
Release Validate native authority/receipt, or use protected-main only with an exact tag/current origin/main SHA, exact-SHA CI, remote-head recheck, and no fresh risk.
Wrong cwd, worktree/git accident, merge recovery, or confusing test/env issue Stop, preserve the review scope, and investigate or validate the existing receipt before proceeding.
Long monolithic session with accumulating complexity Pause and delegate, re-plan, or justify why not.

The workflow guidance directs agents; the native review commands bind receipts and lifecycle gates to the Git candidate they inspect. They protect against accidental scope or identity drift, not a malicious local actor. See the review authority threat model for boundaries and assumptions.


Quick Start

Install (recommended)

macOS / Linux

curl -fsSL https://raw.githubusercontent.com/Gentleman-Programming/gentle-ai/main/scripts/install.sh | bash

Windows (PowerShell)

irm https://raw.githubusercontent.com/Gentleman-Programming/gentle-ai/main/scripts/install.ps1 | iex

The managed installer works with Gentle AI's built-in updater; on Windows it installs to %LOCALAPPDATA%\gentle-ai\bin.

Configure project context

Once your agents are configured, open your AI agent in a project and run these two commands to register the project context:

Command What it does When to re-run
/sdd-init Detects stack, testing capabilities, activates Strict TDD Mode if available When your project adds/removes test frameworks, or first time in a new project
gentle-ai skill-registry refresh Scans installed skills and project conventions, builds the registry After installing/removing skills, or first time in a new project

These are not required for basic usage. The SDD orchestrator runs /sdd-init automatically if it detects no context. Startup hooks normally keep the skill registry fresh for agents that support hooks, including Codex, Claude Code, OpenCode, and Pi through gentle-pi. If you start Pi with pi -ns, startup skill loading/hooks are skipped, so run the registry refresh manually when you need updated project rules.

Run gentle-ai doctor at any time for a read-only health check of your ecosystem (tool binaries, state.json, Engram reachability, disk space).

Alternative install and scope options

Homebrew (macOS / Linux)

brew tap Gentleman-Programming/homebrew-tap
brew trust --formula gentleman-programming/tap/gentle-ai  # one-time, for Homebrew tap trust
brew install gentle-ai

Go install (any platform with Go 1.25.10+)

go install github.com/gentleman-programming/gentle-ai/cmd/gentle-ai@latest

Scoop (Windows) — this is a manual-update path; update it with scoop update gentle-ai.

scoop bucket add gentleman https://github.com/Gentleman-Programming/scoop-bucket
scoop install gentle-ai

By default, gentle-ai install writes agent-scoped files to each selected agent's global config directory. To keep the Gentleman stack isolated to one project, run:

gentle-ai install --scope=workspace

Workspace scope applies to selected agents for agent-scoped files such as system prompts, skills, SDD agents, and persona files. Global-only integrations remain global by design.

Beta channel — use only to test unreleased main builds. It requires Go 1.25.10+:

# macOS / Linux
curl -fsSL https://raw.githubusercontent.com/Gentleman-Programming/gentle-ai/main/scripts/install.sh | bash -s -- --channel beta

# Windows (PowerShell)
$env:GENTLE_AI_CHANNEL="beta"; irm https://raw.githubusercontent.com/Gentleman-Programming/gentle-ai/main/scripts/install.ps1 | iex

Core Workflow

  1. Install and configure. Run the installer, select the agents and components you want, then open your agent in a project.
  2. Plan when it helps. SDD is optional for substantial work. Its artifacts can live in Engram for cross-session memory, OpenSpec for versioned files, or hybrid for both.
  3. Build with discipline. /sdd-init detects project testing capabilities; when Strict TDD is active, SDD apply works test-first. SDD verify audits RED/GREEN evidence and runs verification. Agents that support delegation use focused subagents instead of one growing conversation.
  4. Review one candidate. After implementation, bounded native review freezes the candidate and issues one content-bound receipt. Commit, push, and PR validate that same receipt. Releases validate native authority and its receipt, unless the protected-main fast path has the exact tag/current origin/main SHA, exact-SHA successful CI, a remote-head recheck, and no fresh risk.

Trust what the system can derive, not agent narration. Chapter 21 — Verifiable Trust explains the mental model: agents assess the candidate; native authority and delivery gates independently derive what may be trusted.

  1. Upgrade, then sync. Refresh the binary and the managed agent assets together:

    gentle-ai upgrade
    gentle-ai sync

Review a focused staged candidate

For a monorepo or shared worktree, explicitly review exactly what is in the Git index:

git add apps/my-service
git diff --cached
gentle-ai review start --projection staged

The staged projection freezes the complete existing index, including all previously staged paths. It starts review but does not itself issue an approved receipt; unstaged and untracked worktree content is excluded. The default workspace projection remains the complete workspace review, and an existing authority is never auto-converted between projections. See the review authority threat model for delivery and base-ref details.

Backups

Every install, sync, and upgrade automatically snapshots your config files. Backups are compressed (tar.gz), deduplicated (identical configs are not re-backed up), and auto-pruned (keeps the 5 most recent). Pin important backups via the TUI (p key) to protect them from pruning.

See Backup & Rollback Guide for details.


Key Features You Should Know About

OpenCode SDD Profiles

Assign different AI models to different SDD phases -- a powerful model for design, a fast one for implementation, a cheap one for exploration. OpenCode uses gentle-orchestrator as the base SDD conductor, and generated named profiles still appear as sdd-orchestrator-{name} entries.

# Via CLI
gentle-ai sync --profile cheap:openrouter/qwen/qwen3-30b-a3b:free
gentle-ai sync --profile-phase cheap:sdd-design:anthropic/claude-sonnet-4-20250514

# Or via TUI: gentle-ai → "OpenCode SDD Profiles" → Create

After creating a profile, open OpenCode and press Tab to switch between gentle-orchestrator (default) and your custom profiles.

What you need Use this
Default SDD conductor gentle-orchestrator
Legacy configs sdd-orchestrator is migrated to gentle-orchestrator on sync
Named model profiles sdd-orchestrator-cheap, sdd-orchestrator-premium, etc.

Full guide: OpenCode SDD Profiles

Engram (Persistent Memory)

Your AI agent automatically remembers decisions, bugs, and context across sessions. You don't need to do anything -- but when you do:

engram projects list          # See all projects with memory counts
engram projects consolidate   # Fix name drift ("my-app" vs "My-App")
engram search "auth bug"      # Find a past decision from the terminal
engram tui                    # Visual memory browser

Full reference: Engram Commands


Documentation

Your task Start here
Understand the Gentle-AI mental model Intended Usage
Plan substantial work with SDD Intended Usage and OpenSpec Config
Configure a supported agent Agents for the feature matrix and per-agent notes
Use the Pi package harness Pi Agent for packages, Pi-native commands, models, and troubleshooting
Configure OpenCode phase models OpenCode SDD Profiles
Review or deliver a change safely Review Authority Threat Model for technical boundaries; Chapter 21 — Verifiable Trust for the mental model
Find or share persistent context Engram Commands
Refresh or troubleshoot an installation Usage, Backup & Rollback, and Platforms
Extend or contribute to Gentle AI Components, Skills & Presets, Skill Registry, and Architecture & Development

Community Highlights

This project gets better when the community builds on top of it.

Community Integrations

  • sub-agent-statusline — optional OpenCode TUI plugin that shows sub-agent activity, status, elapsed time, and token/context usage when OpenCode exposes it.
  • sdd-engram-plugin — optional OpenCode TUI plugin to manage SDD profiles and browse Engram memories directly from OpenCode, with runtime profile activation and no restart required.

When you select OpenCode in the installer, Gentle-AI asks whether to register each community plugin and offers a browser shortcut to review the repository first. Gentle-AI only ensures ~/.config/opencode/tui.json exists and adds the plugin package names to its plugin array; OpenCode installs/loads those packages the next time it starts. Once OpenCode has materialized a plugin under ~/.config/opencode/node_modules/, gentle-ai update can compare its local package.json version with the plugin's GitHub releases.

Contributors

This project exists because of the community. See CONTRIBUTORS.md for the full list.


Next Steps


License: MIT

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