feature-spec

star 201

Kicks off a new feature by finding the next incomplete phase in specs/roadmap.md, creating a git branch, interviewing the user about scope/decisions/context, and writing a dated spec directory under specs/ containing plan.md, requirements.md, and validation.md. Trigger when the user says "feature spec", "next phase", "start the next feature", or invokes /feature-spec.

https-deeplearning-ai By https-deeplearning-ai schedule Updated 4/14/2026

name: feature-spec description: Kicks off a new feature by finding the next incomplete phase in specs/roadmap.md, creating a git branch, interviewing the user about scope/decisions/context, and writing a dated spec directory under specs/ containing plan.md, requirements.md, and validation.md. Trigger when the user says "feature spec", "next phase", "start the next feature", or invokes /feature-spec.

Feature Spec

Workflow

1. Find the next phase

Read specs/roadmap.md. The next phase is the first section whose items are all [ ]. Note its name to derive the branch and directory name.

2. Create the branch

git checkout -b phase-N-<kebab-name>

3. Interview the user — BEFORE writing any files

Use AskUserQuestion with exactly 3 questions in one call:

Header Question focus
Scope What the feature collects, exposes, or does — fields, behaviour, data shape
Decisions Key implementation choices — storage, visibility, validation, UX pattern
Context Tone, constraints, or anything shaping the spec — copy style, stack limits, open questions

Do not write any files until the user has answered all three questions.

4. Read guidance files

Read specs/mission.md and specs/tech-stack.md before drafting.

5. Create the spec directory

Name: specs/YYYY-MM-DD-<feature-name>/ using today's date.

requirements.md

  • Scope section: what is and is not included; field/data table if applicable
  • Decisions section: choices made and why (draw from user answers)
  • Context section: tone rules, stack pointers, existing patterns to follow

plan.md

  • Numbered task groups appropriate to the feature (for example: Data → Components → Page & Route → Navigation → Tests)
  • Each group has numbered sub-tasks; groups should be independently implementable

validation.md

  • Automated: project test and typecheck commands pass; specific assertions required
  • Manual: walkthrough, behaviour, edge cases
  • Tone check if the feature has user-facing copy
  • Definition of done

Constraints

  • Respect the existing tech stack defined in specs/tech-stack.md — no new dependencies without user approval
  • Follow existing conventions and patterns already established in the codebase
  • Keep feature scope focused and independently shippable
Install via CLI
npx skills add https://github.com/https-deeplearning-ai/sc-spec-driven-development-files --skill feature-spec
Repository Details
star Stars 201
call_split Forks 190
navigation Branch main
article Path SKILL.md
More from Creator
https-deeplearning-ai
https-deeplearning-ai Explore all skills →