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/feature-forge

@efebc44
by jeffallanjeffallan/claude-skills12k stars
1,124

Conducts structured requirements workshops to produce feature specifications, user stories, EARS-format functional requirements, acceptance criteria, and implementation checklists. Use when defining new features, gathering requirements, or writing specifications. Invoke for feature definition, requirements gathering, user stories, EARS format specs, PRDs, acceptance criteria, or requirement matrices.

Use this Skill: https://skilld.dev/gh/jeffallan/claude-skills/feature-forge

This session only. Nothing lands on disk.

referencespre-discovery-subagents.md

≈521 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Pre-Discovery with Subagents

For features spanning multiple domains (auth, database, UI, etc.) that need front-loaded technical context before the Feature Forge interview.

Overview

For features spanning multiple domains, you can accelerate discovery by launching Task subagents with relevant skills BEFORE starting the Feature Forge interview. This front-loads technical context so the interview focuses on decisions rather than exploration.

When to Use

  • Feature touches 3+ distinct system layers (e.g., auth, database, UI)
  • Codebase is unfamiliar or underdocumented
  • You need concrete technical facts before asking requirements questions
  • Stakeholder time is limited and you want to minimize back-and-forth

When NOT to Use

  • Feature is well-scoped to a single domain
  • You already have deep codebase knowledge
  • Requirements are purely business/UX (no technical exploration needed)

Pattern

1. Identify domains the feature touches
2. Launch parallel Task subagents with relevant skills:
   - Architecture Designer → existing patterns and constraints
   - Framework Expert → current implementation details
   - Security Reviewer → security requirements and risks
3. Collect findings from all subagents
4. Begin Feature Forge interview with technical context loaded
5. Focus interview on decisions, trade-offs, and requirements

Example

For a "user profile with avatar upload" feature:

Task subagent 1 (Architecture Designer):
  "Analyze the current user model, storage patterns, and image handling in this codebase"

Task subagent 2 (Security Reviewer):
  "What security concerns exist for file upload in this stack?"

Task subagent 3 (Framework Expert):
  "How does this project handle API endpoints and file storage?"

Results feed into the Feature Forge interview, so questions like "Where should we store avatars?" come with context about existing patterns.

Integration with Interview Questions

See interview-questions.md for the full multi-agent discovery pattern and how subagent findings map to interview categories.

Source: SKILL.md on GitHub

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Signed by skilld at efebc44. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 months ago.

Steadyupdated 5 months ago
Other metadata
metadata
{
  "author": "https://github.com/Jeffallan",
  "version": "1.1.0",
  "domain": "workflow",
  "triggers": "requirements, specification, feature definition, user stories, EARS, planning",
  "role": "specialist",
  "scope": "design",
  "output-format": "document",
  "related-skills": "fullstack-guardian, spec-miner, test-master"
}
  • requirements
  • specification
  • user-stories
  • ears
  • acceptance-criteria
  • planning
  • prd
  • workshop
  • feature-definition

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Conducts structured requirements workshops using PM and Dev perspectives to produce feature specifications, EARS-format functional requirements, acceptance criteria, and implementation checklists. Targets feature definition, requirements gathering, and specification writing workflows with systematic discovery and validation phases.

Generated from the current SKILL.md.

Does this skill write the spec automatically, or does it require user input?
It requires structured user input through interviews and discovery questions. The skill conducts a systematic workshop using the AskUserQuestions tool to gather requirements before producing the specification.
What output formats does this skill produce?
It produces EARS-format functional requirements, Given/When/Then acceptance criteria, non-functional requirements, error handling tables, and implementation TODO checklists, all saved as a markdown specification document.
Can this skill handle complex features that span multiple domains?
Yes. The skill includes guidance for using multi-agent discovery with Task subagents on features spanning multiple domains, documented in the pre-discovery-subagents reference.
Does this skill cover non-functional requirements like performance and security?
Yes. It explicitly requires inclusion of non-functional requirements, security considerations, and error handling as part of the specification output.

Generated from the current SKILL.md. These answers refresh after source changes.