EasyPlatform create-feature

[Implementation] Scaffold a new feature with backend and frontend components

install
source · Clone the upstream repo
git clone https://github.com/duc01226/EasyPlatform
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/duc01226/EasyPlatform "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills/create-feature" ~/.claude/skills/duc01226-easyplatform-create-feature && rm -rf "$T"
manifest: .claude/skills/create-feature/SKILL.md
source content

[IMPORTANT] Use

TaskCreate
to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

<!-- SYNC:critical-thinking-mindset -->

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

<!-- /SYNC:critical-thinking-mindset --> <!-- SYNC:ai-mistake-prevention -->

AI Mistake Prevention — Failure modes to avoid on every task:

  • Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal.
  • Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing.
  • Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain.
  • Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path.
  • When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site.
  • Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code.
  • Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks.
  • Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis.
  • Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly.
  • Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.
<!-- /SYNC:ai-mistake-prevention -->

Prerequisites: MUST ATTENTION READ before executing:

<!-- SYNC:understand-code-first -->

Understand Code First — HARD-GATE: Do NOT write, plan, or fix until you READ existing code.

  1. Search 3+ similar patterns (
    grep
    /
    glob
    ) — cite
    file:line
    evidence
  2. Read existing files in target area — understand structure, base classes, conventions
  3. Run
    python .claude/scripts/code_graph trace <file> --direction both --json
    when
    .code-graph/graph.db
    exists
  4. Map dependencies via
    connections
    or
    callers_of
    — know what depends on your target
  5. Write investigation to
    .ai/workspace/analysis/
    for non-trivial tasks (3+ files)
  6. Re-read analysis file before implementing — never work from memory alone
  7. NEVER invent new patterns when existing ones work — match exactly or document deviation

BLOCKED until:

- [ ]
Read target files
- [ ]
Grep 3+ patterns
- [ ]
Graph trace (if graph.db exists)
- [ ]
Assumptions verified with evidence

<!-- /SYNC:understand-code-first -->

Quick Summary

Goal: Scaffold a new full-stack feature with backend (entities, CQRS, controllers) and frontend (Angular components, services).

Workflow:

  1. Analyze — Break down requirements, identify scope (backend/frontend/full-stack)
  2. Identify — Determine target microservice and Angular app/module
  3. Plan — Map out entities, commands/queries, endpoints, components, DTOs
  4. Approve — Present plan, wait for explicit user approval before creating files
  5. Create — Scaffold files in order: entities → application → DTOs → controllers → frontend

Key Rules:

  • DO NOT proceed without explicit user approval
  • Follow platform patterns from CLAUDE.md and
    .github/prompts/
    templates
  • Build order: Domain → Application → API → Frontend
  • Verify with
    dotnet build
    and
    nx build
    after creation

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Create a new feature: $ARGUMENTS

Steps:

  1. Analyze Requirements

    • Break down the feature requirements
    • Identify the scope (backend only, frontend only, or full-stack)
  2. Identify Service Location

    • Determine the appropriate microservice for backend
    • Identify the Angular app/module for frontend
  3. Plan Implementation

    • Domain entities needed
    • CQRS Commands/Queries
    • API endpoints (controllers)
    • Angular components and services
    • DTOs and validation
  4. Use Project Patterns

    • Reference patterns from CLAUDE.md
    • Use
      .github/prompts/
      templates for scaffolding:
      • create-cqrs-command.prompt.md
      • create-cqrs-query.prompt.md
      • create-entity-event.prompt.md
      • create-angular-component.prompt.md
      • create-api-service.prompt.md
  5. Wait for Approval

    • Present the implementation plan
    • DO NOT proceed without explicit approval
  6. Create Files (After Approval) Execute in this order:

    1. Domain entities (
      .Domain/Entities/
      )
    2. Application layer (
      .Application/UseCaseCommands/
      ,
      .Application/UseCaseQueries/
      )
    3. Entity DTOs (
      .Application/EntityDtos/
      )
    4. API controllers (
      .Api/Controllers/
      )
    5. Frontend components and services
  7. Verify

    • Build backend:
      dotnet build
    • Build frontend:
      nx build <app-name>

Closing Reminders

  • MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using
    TaskCreate
    BEFORE starting
  • MANDATORY IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
  • MANDATORY IMPORTANT MUST ATTENTION cite
    file:line
    evidence for every claim (confidence >80% to act)
  • MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
  • MANDATORY IMPORTANT MUST ATTENTION validate decisions with user via
    AskUserQuestion
    — never auto-decide MANDATORY IMPORTANT MUST ATTENTION READ the following files before starting: <!-- SYNC:understand-code-first:reminder -->
  • MANDATORY IMPORTANT MUST ATTENTION search 3+ existing patterns and read code BEFORE any modification. Run graph trace when graph.db exists. <!-- /SYNC:understand-code-first:reminder --> <!-- SYNC:critical-thinking-mindset:reminder -->
  • MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact. <!-- /SYNC:critical-thinking-mindset:reminder --> <!-- SYNC:ai-mistake-prevention:reminder -->
  • MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction. <!-- /SYNC:ai-mistake-prevention:reminder -->