One CLI to replace scattered prompts, manual task tracking, and copy-paste review cycles. Compozy drives the full lifecycle of AI-assisted development: product ideation, technical specification, task breakdown with codebase-informed enrichment, concurrent execution across agents, and automated PR review remediation.

• One command, 40+ agents. Install bundled skills into Claude Code, Codex, Cursor, Droid, OpenCode, Pi, Gemini, and 40+ other agents and editors with compozy setup.
• Idea to code in a structured pipeline. Optional Issue → PRD → TechSpec → Tasks → Execution → Review. Each phase produces plain markdown artifacts that feed into the next. Start from an issue for full research and debate, or jump straight to PRD if you already have a clear scope.
• Codebase-aware enrichment. Tasks aren't generic prompts. Compozy spawns parallel agents to explore your codebase, discover patterns, and ground every task in real project context.
• Multi-agent execution. Run tasks through ACP-capable runtimes like Claude Code, Codex, Cursor, Droid, OpenCode, Pi, or Gemini — just change --ide. Concurrent batch processing with configurable timeouts, retries, and exponential backoff, all with a live terminal UI.
• Workflow memory between runs. Agents inherit context from every previous task — decisions, learnings, errors, and handoffs. Two-tier markdown memory with automatic compaction keeps context fresh without manual bookkeeping.
• Provider-agnostic reviews. Fetch review comments from CodeRabbit, GitHub, or run AI-powered reviews internally. All normalize to the same format. Provider threads resolve automatically after fixes.
• Markdown everywhere. PRDs, specs, tasks, reviews, and ADRs are human-readable markdown files. Version-controlled, diffable, editable between steps. No vendor lock-in.
• Frontmatter for machine-readable metadata. Tasks and review issues keep parseable metadata in standard YAML frontmatter instead of custom XML tags.
• Single binary, local-first. Compiles to one Go binary with zero runtime dependencies. Your code and data stay on your machine.
• Embeddable. Use as a standalone CLI or import as a Go package into your own tools.

brew tap compozy/compozy
brew install --cask compozy

npm install -g @compozy/cli

go install github.com/compozy/compozy/cmd/compozy@latest

git clone git@github.com:compozy/compozy.git
cd compozy && make verify && go build ./cmd/compozy

Then install bundled skills into your AI agents:

compozy setup          # interactive — pick agents and skills
compozy setup --all    # install everything to every detected agent

Execution runtimes are separate from skill installation. To run compozy start or compozy fix-reviews, install an ACP-capable runtime or adapter on PATH for the --ide you choose:

When the direct ACP command is not installed, Compozy can also fall back to supported launchers such as npx @zed-industries/codex-acp when the launcher is available locally.

Every artifact is a plain markdown file in .compozy/tasks/<name>/. You can read, edit, or version-control any of them between steps.

Task and review issue files use YAML frontmatter for parseable metadata such as status, domain, severity, and provider_ref. Task workflow _meta.md files can be refreshed explicitly with compozy sync. Fully completed workflows can be moved out of the active task root with compozy archive. If you have an older project with XML-tagged artifacts, run compozy migrate once before using start or fix-reviews.

Compozy can load project defaults from .compozy/config.toml.

• The CLI discovers the nearest .compozy/ directory by walking upward from the current working directory.
• If .compozy/config.toml exists, Compozy loads it once at command startup.
• Interactive forms for compozy start, compozy fix-reviews, and compozy fetch-reviews are prefilled from the resolved config.
• Explicit CLI flags always win over config values.

Precedence is:

explicit flags > command section > [defaults] > built-in defaults

Example:

[defaults]
ide = "codex"
model = "gpt-5.4"
reasoning_effort = "medium"
access_mode = "full"
timeout = "10m"
tail_lines = 0
add_dirs = ["../shared"]
auto_commit = false
max_retries = 0
retry_backoff_multiplier = 1.5

[start]
include_completed = false

[fix_reviews]
concurrent = 2
batch_size = 3
grouped = true
include_resolved = false

[fetch_reviews]
provider = "coderabbit"

Supported sections in v1:

• [defaults] for shared execution defaults such as ide, model, reasoning_effort, access_mode, timeout, tail_lines, add_dirs, auto_commit, max_retries, and retry_backoff_multiplier
• [start] for include_completed
• [fix_reviews] for concurrent, batch_size, grouped, and include_resolved
• [fetch_reviews] for provider

Notes:

• .compozy/config.toml is optional. If it is absent, Compozy keeps the current built-in defaults.
• .compozy/tasks remains the fixed workflow root in this version; the config file does not change the workflow root path.
• Unknown keys and invalid value types are rejected during config loading.
• max_retries applies to execution-stage ACP failures and inactivity timeouts for both compozy start and compozy fix-reviews.
• retry_backoff_multiplier only increases the next attempt timeout; retries restart immediately and do not add a sleep delay.

This walkthrough builds a feature called user-auth from idea to shipped code.

compozy setup

Auto-detects installed agents and copies (or symlinks) skills into their configuration directories. compozy start and compozy fix-reviews now verify that bundled Compozy skills are installed for the selected agent before running. Missing installs block the run, and outdated installs prompt for refresh in interactive terminals.

Inside your AI agent (Claude Code, Codex, Cursor, OpenCode, Pi, etc.):

/cy-idea-factory user-auth

Transforms a raw idea into a structured issue spec — asks targeted questions, researches market and codebase in parallel, runs business analysis and council debate, suggests high-leverage alternatives, and produces a research-backed issue. Skip this step if you already have a clear feature scope.

/cy-create-prd user-auth

Interactive brainstorming session — reads the issue if one exists, asks clarifying questions, spawns parallel agents to research your codebase and the web, produces a business-focused PRD with ADRs.

/cy-create-techspec user-auth

Reads your PRD, explores the codebase architecture, asks technical clarification questions. Produces architecture specs, API designs, and data models.

/cy-create-tasks user-auth

Analyzes both documents, explores your codebase for relevant files and patterns, produces individually executable task files with status tracking, context, and acceptance criteria.

compozy start --name user-auth --ide claude

Each pending task is processed sequentially — the agent reads the spec, implements the code, validates it, and updates the task status. Use --dry-run to preview prompts without executing.

Option A — AI-powered review inside your agent:

/cy-review-round user-auth

Option B — Fetch from an external provider:

compozy fetch-reviews --provider coderabbit --pr 42 --name user-auth

Both produce the same output: .compozy/tasks/user-auth/reviews-001/issue_*.md

compozy fix-reviews --name user-auth --ide claude --concurrent 2 --batch-size 3

Agents triage each issue as valid or invalid, implement fixes for valid issues, and update statuses. Provider threads are resolved automatically.

Repeat steps 7–8. Each cycle creates a new review round (reviews-002/, reviews-003/), preserving full history. When clean — merge and ship.

Compozy bundles 9 skills that its workflows depend on. They run inside your AI agent — no context switching to external tools.

When agents execute tasks, context gets lost between runs — decisions made, errors hit, patterns discovered. Compozy solves this with a two-tier memory system that gives each agent a running history of the workflow.

Every task execution automatically bootstraps two markdown files inside .compozy/tasks/<name>/memory/:

How it works:

1. Before a task runs, Compozy creates the memory directory and scaffolds both files with section templates if they don't exist yet.
2. The agent reads both memory files before writing any code — treating them as mandatory context, not optional notes.
3. During execution, the agent keeps task memory current: decisions, learnings, errors, and corrections.
4. Only durable, cross-task context gets promoted to shared memory. Task-local details stay in the task file.
5. Before completion, the agent updates memory with anything that helps the next run start faster.

Automatic compaction. Memory files have soft limits (150 lines / 12 KB for shared, 200 lines / 16 KB per task). When a file exceeds its threshold, Compozy flags it for compaction — the agent trims noise and repetition while preserving active risks, decisions, and handoffs.

No duplication. Memory files don't copy what's already in the repo, git history, PRD, or task specs. They capture only what would otherwise be lost between runs: the why behind decisions, surprising findings, and context that makes the next agent immediately productive.

The cy-workflow-memory skill handles all of this automatically when referenced in task prompts. No manual setup required — just run compozy start and agents inherit context from every previous run.

Execution (compozy start, compozy fix-reviews) — ACP-capable runtimes that can run tasks:

Skill installation (compozy setup) — 40+ agents and editors, including Claude Code, Codex, Cursor, Droid, OpenCode, Pi, Gemini CLI, GitHub Copilot, Windsurf, Amp, Continue, Goose, Roo Code, Augment, Kiro CLI, Cline, and many more. Run compozy setup to see all detected agents on your system.

When installing to multiple agents, Compozy offers two modes:

• Symlink (default) — One canonical copy with symlinks from each agent directory. All agents stay in sync.
• Copy — Independent copies per agent. Use --copy when symlinks are not supported.

compozy setup [flags]

compozy migrate [flags]

compozy sync [flags]

compozy archive [flags]

compozy start [flags]

compozy fetch-reviews [flags]

compozy fix-reviews [flags]

// Prepare work without executing
prep, err := compozy.Prepare(context.Background(), compozy.Config{
    Name:     "multi-repo",
    TasksDir: ".compozy/tasks/multi-repo",
    Mode:     compozy.ModePRDTasks,
    DryRun:   true,
})

// Fetch reviews and run remediation
_, _ = compozy.FetchReviews(context.Background(), compozy.Config{
    Name:     "my-feature",
    Provider: "coderabbit",
    PR:       "259",
})

// Preview a legacy artifact migration
_, _ = compozy.Migrate(context.Background(), compozy.MigrationConfig{
    DryRun: true,
})

_ = compozy.Run(context.Background(), compozy.Config{
    Name:            "my-feature",
    Mode:            compozy.ModePRReview,
    IDE:             compozy.IDECodex,
    ReasoningEffort: "medium",
})

// Embed the Cobra command in another CLI
root := command.New()
_ = root.Execute()

cmd/compozy/             CLI entry point
command/                 Public Cobra wrapper for embedding
internal/cli/            Cobra flags, interactive form, CLI glue
internal/core/           Internal facade for preparation and execution
  agent/                 IDE command validation and process construction
  memory/                Workflow memory bootstrapping, inspection, and compaction detection
  model/                 Shared runtime data structures
  plan/                  Input discovery, filtering, grouping, batch prep
  prompt/                Prompt builders emitting runtime context + skill names
  run/                   Execution pipeline, logging, shutdown, Bubble Tea UI
internal/setup/          Bundled skill installer (agent detection, symlink/copy)
internal/version/        Build metadata
skills/                  Bundled installable skills
.compozy/config.toml     Optional workspace defaults for CLI execution
.compozy/tasks/          Default workflow artifact root (PRDs, TechSpecs, tasks, ADRs, reviews)

make verify    # Full pipeline: fmt → lint → test → build
make fmt       # Format code
make lint      # Lint (zero tolerance)
make test      # Tests with race detector
make build     # Compile binary
make deps      # Tidy and verify modules

Contributions are welcome. See CONTRIBUTING.md for guidelines.

MIT