auto-plan

Coordinate six-cycle autonomous planning pipelines for AI agent features.

Updated May 13, 2026
One-click install
npx skills add https://github.com/usetheodev/theo-ui --skill auto-plan-usetheodev
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: auto-plan
Source: https://github.com/usetheodev/theo-ui/tree/main/.claude/skills/auto-plan
Command: npx skills add https://github.com/usetheodev/theo-ui --skill auto-plan-usetheodev

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pyyaml, and includes scripts (resource) components.

What problem does it solve?

Orchestrates end-to-end autonomous planning for AI agent workflows, coordinating the 6-cycle pipeline (cycle-discover, cycle-plan, cycle-implement, cycle-code-quality, cycle-review, cycle-release) from a single invocation to deliver a release-ready plan and artifact set.

Core Features & Use Cases

  • Coordinates the entire planning sequence, including discover, plan, attest, implement, code-quality, review, and release, with deterministic depth decisions.
  • Supports roadmap-driven and ad-hoc topic workflows, injects MUST-FIX items automatically into plans, and annotates milestones for roadmap alignment.
  • Enforces governance gates (confidence, plan quality, code-quality) and produces auditable outputs and artifacts for release.

Quick Start

Use the /auto-plan command to orchestrate the full feature pipeline end-to-end with autonomous depth selection.

Frequently Asked Questions about auto-plan

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate end-to-end planning for AI agent features from idea to PR?▼

Autonomous end-to-end planning is automated by coordinating a 6-cycle pipeline covering discovery, planning, implementation, code quality, review, and release to deliver release-ready artifacts from a single invocation.

What is the best way to enforce governance gates and human approval in an autonomous workflow?▼

Governance gates are enforced during the release cycle by applying confidence, plan quality, and code-quality checks, requiring human approval and attestations to ensure safe, auditable delivery before release.

Does autonomous planning work with ad-hoc topics or does it require a predefined roadmap?▼

Autonomous planning supports both roadmap-driven and ad-hoc topic workflows, automatically deriving depth, annotating milestones for roadmap alignment, and injecting MUST-FIX items into the generated plans.

How do I start orchestrating the full feature pipeline with autonomous depth selection?▼

You start orchestrating the full feature pipeline by invoking the /auto-plan command, which triggers deterministic depth decisions across the discover, plan, implement, and release cycles automatically.

Do I need to install PyYAML to run the autonomous planning pipeline?▼

Yes, PyYAML is required as a dependency to run the autonomous planning pipeline, as the scripts component relies on it to process workflow configurations and milestone metadata.

What limitations exist when adding MUST-FIX items to ad-hoc topic plans?▼

MUST-FIX items are automatically injected into plans based on deterministic depth decisions and governance gates, meaning plan adjustments are constrained by confidence levels and required code-quality checks before release.