spec-creation

Feature specification creation from codebase research. Produces requirements, acceptance criteria, architecture decisions, implementation plans, and risk analysis.

509 stars

Best use case

spec-creation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Feature specification creation from codebase research. Produces requirements, acceptance criteria, architecture decisions, implementation plans, and risk analysis.

Teams using spec-creation should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/spec-creation/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/methodologies/claudekit/skills/spec-creation/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/spec-creation/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How spec-creation Compares

Feature / Agentspec-creationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Feature specification creation from codebase research. Produces requirements, acceptance criteria, architecture decisions, implementation plans, and risk analysis.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Spec Creation

## Overview

Creates comprehensive feature specifications by first deeply researching the codebase, then generating structured specifications with requirements, acceptance criteria, architecture decisions, and phased implementation plans.

## Research Phase

- Analyze project structure and module organization
- Identify existing patterns and conventions
- Map dependencies and integration points
- Review existing tests for testing patterns
- Document technical constraints

## Specification Components

### Scope and Non-Goals
Clear boundaries on what the feature does and does not include.

### Functional Requirements
Detailed requirements with unique identifiers for tracking.

### Acceptance Criteria
Testable, measurable criteria for each requirement.

### Architecture Decisions
Decision records with rationale and alternatives considered.

### Implementation Plan
Phased approach ordered by dependency, not priority.

### Risk Analysis
Identified risks with probability, impact, and mitigation strategies.

### API Contracts and Data Models
Interface definitions and data model schemas.

### Test Strategy
Mapping of unit, integration, and E2E tests to requirements.

## Output

Specifications are saved to `docs/specs/{feature}.md` for reference by the execution workflow.

## When to Use

- `/spec:create [feature]` slash command
- Before starting a new feature implementation
- When planning complex multi-module changes

## Processes Used By

- `claudekit-spec-workflow` (create mode)