agentleFS
sankar2codesankar2code/Claude-Skill_SubAgent-Builder-Collections/skills/engineering-planner/SKILL.md

engineering-planner

Skill2 starsChanged 36 days agoMITView on GitHub

Transforms a PRD, product brief, feature request, or project description into a comprehensive Engineering Document (High-Level Design). Trigger when a user asks to create an engineering document, engineering doc, HLD, system architecture, technical design, or wants to convert requirements into a technical plan. The output defines the architecture, tech stack, core components, data flow, APIs, database design, integrations, security considerations, deployment approach, and implementation roadmap before development begins, as a single file: docs/engineering/engineering-doc.md. Stage 1 of the PRD → Production pack.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Write this file with these sections in order:

    line 37
  2. Distinctive:

    No vague statements — every section must be concrete and actionable

    line 61

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

PRD → Production pack · Stage 1 of 5. engineering-planner → implementation-specs → security-foundation → frontend-setup → build features (with design-system always on) Stop after this stage, show the user what was produced, and wait for approval before moving on.

Default stack: Next.js (App Router) + TypeScript on the frontend, Supabase (Postgres, Auth, Storage) on the backend. Do not ask about the frontend framework. If the PRD names a different backend, database or LLM provider, use what the PRD says.


Input

A PRD (Product Requirements Document) provided by the user — pasted text, a file path, or an uploaded document.


Steps

  1. Analyze the PRD — extract functional requirements, non-functional requirements, and gaps.
  2. Resolve open decisions — if the PRD leaves an architectural decision open (auth strategy, user roles, LLM provider, file storage, payments), ask the user before writing. Never assume.
  3. Generate docs/engineering/engineering-doc.md (high-level architecture doc).

Output: docs/engineering/engineering-doc.md

Write this file with these sections in order:

  1. Executive Summary — project name, business goal, problem statement, target users, success criteria
  2. Product Scope — in scope / out of scope / future enhancements
  3. User Personas — user types, responsibilities, permissions, primary workflows
  4. User Flows — every major journey (signup, login, dashboard, AI chat, file upload, search, payments, admin) using the format:
    User Action → Frontend Behavior → Backend Processing → Database Interaction → System Response
  5. Frontend Architecture — Next.js stack (UI lib, state management, routing strategy), UX states (loading/empty/error/responsive/a11y), page and component hierarchy
  6. Backend Architecture — stack, core systems (auth, authz, business logic, validation, middleware, error handling), service interaction diagram
  7. Database Design and schema — per table: purpose, columns + types, relationships, constraints, indexes
  8. AI Architecture (only if AI features exist) — LLM provider, model, prompt strategy, context/memory, token limits, rate limiting, cost controls, fallback
  9. API Specification — per endpoint: method, path, purpose, auth required, request schema, response schema, validation rules, error responses
  10. Feature Breakdown — Phase 1 (MVP), Phase 2, Phase 3 — each with: feature description, acceptance criteria, dependencies
  11. Folder Structure — production-ready directory layout with purpose annotations
  12. Naming Conventions — files, folders, components, hooks, services, APIs, DB tables, env vars, config files — with examples
  13. Testing Strategy — unit, integration, and E2E with recommended frameworks and coverage targets
  14. Specs to Implementation Mapping — for each spec, list the corresponding implementation files and the full flow from spec to code

Requirements

  • No vague statements — every section must be concrete and actionable
  • Include Mermaid or ASCII diagrams where architecture benefits from visual representation
  • engineering-doc.md is the authoritative reference; no implementation begins until it is approved

When done

Show the user the document and ask:

"The engineering document is ready at docs/engineering/engineering-doc.md. Review it and let me know when you're happy to move to Stage 2 — Implementation Specs (implementation-specs)."

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.