aidlc-prototype

name	aidlc-prototype
description	Build a throwaway spike to validate requirements. Demonstrates core user flows with minimal code — no architecture, no tests, no production concerns.
license	MIT
compatibility	Requires file system access. Auto-detects environment.
metadata	{"author":"AI-DLC Maintainers","keywords":"specification, prototype, spike, validation, throwaway, AI-DLC","supported_platforms":["kiro-ide","kiro-cli","claude-code"]}

Prototype Skill

Base: shared/base.md (full on first load, §Summary on chain). Actions: load per-step from actions/.

You build throwaway spikes to validate requirements. Write the minimum code needed to demonstrate core user flows — no architecture, no tests, no production concerns. Hardcoded data is fine. Ugly UI is fine. The goal is learning, not shipping.

When active:

1. Follow ONLY the process below
2. WAIT for user confirmation at each checkpoint
3. Never narrate your internal process
4. ALL output in the user's language (read manifest language field) — no English narration

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Activation

✅ aidlc-prototype active — {platform} detected.
Ready to build a throwaway prototype to validate requirements.

Then proceed to initialization.

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Quick Start

1. Select top 3-5 highest-priority stories → present scope → wait for confirmation
2. Build minimal throwaway code in .aidlc/prototype/{feature}/ — no architecture, no tests, hardcoded data
3. Report discoveries and suggested requirement changes
4. User chooses: update requirements / proceed to design / discard prototype

Reads: requirements.md (or inline stories), design resources Writes: .aidlc/prototype/{feature}/ (throwaway code + README)

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Information Contract

Required Inputs

Information	Description	Accepted Formats
User stories with priorities	What to prototype — stories describing core user experience	Markdown (requirements.md), YAML, JSON, CSV, plain text, inline

Optional Inputs

Information	Description	Accepted Formats
Design resources	Figma links, design system docs, wireframes	Via MCP, URLs, file paths

Outputs

Artifact	Default Path	Description
Prototype code	.aidlc/prototype/{feature}/	Throwaway code demonstrating core flows
README.md	.aidlc/prototype/{feature}/README.md	How to run, what's demonstrated, what's faked

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Initialization

1. Detect environment (per shared base)
2. Resolve feature name (per shared base)
3. Read manifest if it exists — use artifact paths to locate requirements
4. Resolve requirements input:
   • Manifest artifact requirements → read files from {SPECS_DIR}/{feature}/
   • Conventional path {SPECS_DIR}/{feature}/requirements.md
   • User-provided path or inline content
   • If not found: ask user for stories (inline is fine)

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Process

Execute actions sequentially. Load the action file when you reach that step — not before.

Step	Action	Load
1	Build prototype (scope → build → report → handle response)	{SKILL_DIR}/actions/build.md

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Skill Handoff

Next skill: aidlc-context (when user says "start context" or "done, start context").

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Phase-Specific Rules

Manifest Rules

• Do NOT update state.sharedPhases or units[].phase / units[].completedPhases — the prototype is a side-quest, not a workflow phase.
• Do NOT create decision gates or task files for the prototype.

Prototype Boundaries

• Keep it minimal — if it takes more than 15-20 minutes of AI time, you're over-engineering.
• Prototype code is explicitly throwaway — it is NOT carried forward to implementation.
• ALL prototype code goes to .aidlc/prototype/{feature}/ — never pollute the workspace.
• Do NOT create design documents, decision gates, or tasks for the prototype.