flow-auto

Automate the SDLC workflow from planning to merge-ready PR.

4|Updated Mar 24, 2026
One-click install
npx skills add https://github.com/skaisser/blueprint --skill flow-auto
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: flow-auto
Source: https://github.com/skaisser/blueprint/tree/main/skills/flow-auto
Command: npx skills add https://github.com/skaisser/blueprint --skill flow-auto

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the manual SDLC workflow, eliminating context drift and bottlenecks caused by waiting for user input.

Core Features & Use Cases

  • End-to-end automation of plan, execute, review, and PR steps
  • Zero-intervention operation with autonomous decision-making
  • Guaranteed progress with checkpointed stages and green gate tests
  • Robust rollback and audit trails for traceability

Quick Start

Invoke the flow-auto skill with your task description to start the full autonomous SDLC pipeline.

Frequently Asked Questions about flow-auto

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

FAQPage Schema
How do I automate the entire SDLC pipeline from planning to pull request?

You can automate the SDLC pipeline by invoking an autonomous workflow that handles planning, executing, reviewing, testing, and creating a merge-ready PR without requiring manual user decisions.

What is an autonomous software development lifecycle workflow?

An autonomous SDLC workflow is an automated pipeline that executes planning, coding, and review stages independently, enforcing strict merge readiness criteria like green tests and generating a clear final report.

How do I create a merge-ready pull request with guaranteed green tests?

To create a merge-ready pull request, an automated pipeline enforces green gate tests, checkpoints progress, and applies strict merge readiness criteria before finalizing the PR for review.

Can I run an automated pipeline without manual intervention during code review?

Yes, the autonomous pipeline operates with zero-intervention, making independent decisions during code review and executing rollback protocols if necessary to ensure robust traceability.

What is the best way to track progress in an automated pull request pipeline?

The best way to track progress in an automated pipeline is using checkpointed stages that guarantee forward progress and maintain robust audit trails for full traceability.

Why does my autonomous SDLC pipeline stall waiting for user input?

An SDLC pipeline stalls due to manual context drift and bottlenecks, which you can eliminate by deploying an autonomous workflow that makes zero-intervention decisions end-to-end.