What is a spec pipeline in Auto-Claude?

It is a series of automated phases—such as Discovery, Research, and Context—that transform a simple task description into a detailed technical specification and actionable plan.

Can I resume a spec creation if it is interrupted?

Yes, you can use the --continue flag followed by the spec ID to resume the process from the last completed phase without losing progress.

What files are generated in a spec directory?

The skill generates a spec.md file for human review, along with JSON files for requirements, context, research, and a subtask-based implementation plan.

How does the skill handle different task complexities?

It dynamically selects between 3 to 8 phases. Simple tasks focus on quick specs, while complex tasks trigger additional research, self-critique, and deeper context analysis.

Auto-Claude Spec Manager

Name: Auto-Claude Spec Manager
Author: adaptationio

byadaptationio

Productivity & Workflow

Automates the creation and management of detailed technical specifications and implementation plans for autonomous software builds.

About

Auto-Claude Spec Manager provides a structured pipeline for transforming high-level feature ideas into production-ready specifications. By automating discovery, requirement gathering, and codebase context analysis, it ensures that AI-driven development processes have all the necessary information to execute complex builds successfully. The skill dynamically adapts its pipeline phases based on task complexity, ensuring technical accuracy, clear acceptance criteria, and actionable implementation plans for everything from minor UI tweaks to major architectural overhauls.

Key Features

Dynamic pipeline selection (Discovery, Requirements, Research, Context, Spec, Plan, Critique, Validation)
Automated codebase analysis to identify affected components and dependencies
Self-critique and validation phases for complex architectural changes
Structured output generation including Markdown specs and JSON implementation plans
0 GitHub stars
Interactive requirement gathering to clarify scope and constraints

Use Cases

Validating external API compatibility and technical constraints before starting an autonomous build
Generating comprehensive implementation plans for complex codebase migrations
Transforming vague feature requests into structured, testable technical requirements

About

Key Features

Dynamic pipeline selection (Discovery, Requirements, Research, Context, Spec, Plan, Critique, Validation)
Automated codebase analysis to identify affected components and dependencies
Self-critique and validation phases for complex architectural changes
Structured output generation including Markdown specs and JSON implementation plans
0 GitHub stars
Interactive requirement gathering to clarify scope and constraints

Use Cases

Validating external API compatibility and technical constraints before starting an autonomous build
Generating comprehensive implementation plans for complex codebase migrations
Transforming vague feature requests into structured, testable technical requirements