Tech Stack

Technology Stack Decision Guide

Guide me through selecting a technology stack for this project using a collaborative, educational approach.

Project Context

$ARGUMENTS

Your Approach

For each technology category:

1. Present 2-4 viable options with clear explanations (avoid jargon where possible)
2. Explain tradeoffs in accessible language covering:

• Learning curve - how quickly can I understand and work with this?
• Maintenance burden - ongoing effort to keep it running
• Cost - monthly operational costs
• Community support - documentation and help availability
• How it fits with other decisions we've made

1. Wait for my questions before proceeding - this is a learning conversation
2. Provide context about why certain options fit this specific project's needs
3. After I decide, document the decision with rationale

Decision Categories

Work through these in order, skipping any that don't apply to this project:

1. Backend Language & Framework
2. Database
3. Frontend Framework
4. Local Development Environment
5. Hosting Platform & Deployment Environments
6. File/Document Storage
7. Email Service
8. Authentication Strategy
9. AI Inference & Governance (if project uses AI/LLM)
10. Testing Framework
11. UI/UX Foundations

Category-Specific Notes

4. Local Development Environment Ask: Mac, Windows, Linux, or mixed team? Using Docker for local dev? WSL for Windows?

Common cross-platform issues to discuss:

• Path separators (/ vs \) → use path.join() or forward slashes
• Line endings (LF vs CRLF) → configure .gitattributes
• Case sensitivity → be consistent with import casing
• Shell scripts → use npm scripts or cross-env for portability
• Native dependencies → Docker or pre-built binaries help
• Docker mounts on Windows → slower without WSL2

5. Hosting Platform & Deployment Environments First ask: How many environments? Options:

• Local-only (prototyping)
• Dev + Prod (small projects)
• Dev + Staging + Prod (production apps)

Then ask hosting preference. Important: If local dev OS differs from production OS and they're not using containers, flag this as a risk—recommend Docker or CI/CD testing on the target platform.

9. AI Inference & Governance Only applicable if the project uses AI/LLM capabilities. Skip entirely for pure-software projects.

This category produces TWO technology decisions:

• TD-XXX — AI Inference: Which model(s), which provider, streaming, cost constraints (standard tech decision)
• TD-XXX — AI Boundary Classification: Where AI belongs in this app and where it doesn't (governance decision)

For the AI Boundary Classification decision, walk through every planned feature and classify each component:

| Classification | Definition | Governance Requirement | |---------------|------------|----------------------| | DETERMINISTIC | Code executes it identically every time. No AI. | Standard software testing. This is the default — everything is DETERMINISTIC unless there's a reason it can't be. | | AI-ADVISORY | AI generates output that a human reviews before acting. | Acceptable risk. Note who reviews. | | AI-OPERATIONAL | AI generates output the system or user acts on without full review. | Highest risk. Must specify: (1) deterministic pre-validator, (2) schema enforcement, (3) post-execution audit mechanism. |

Key questions to ask:

1. "Which features in this app will use AI?" — List them.
2. For each: "Can this logic be fully specified as rules?" If yes → DETERMINISTIC. Don't use AI for things you can code.
3. For each: "Who acts on this output?" If a human reviews → AI-ADVISORY. If the system acts automatically → AI-OPERATIONAL.
4. For each AI-OPERATIONAL component: "What happens if the output is wrong?" Define the gating requirements.

Anti-patterns to flag during this discussion:

• AI doing math, totals, date calculations, unit conversions → always code these
• AI enforcing business rules or compliance checks → code the rules; use AI to audit
• AI controlling workflow sequence → use state machines; let AI advise within a step
• Externally-sourced constants (formulas, rates, regulatory values) without a verification reference → require verified_against provenance

Record the decision as:

### TD-XXX — AI Boundary Classification

- **Decision**: AI boundary classification for [project name]
- **Date**: [date]
- **Rationale**: [Why these boundaries were drawn here]

**AI-OPERATIONAL components** (require gating):
| Component | Pre-validator | Schema enforcement | Post-audit |
|-----------|--------------|-------------------|------------|
| [name]    | [what checks] | [Pydantic/JSON schema] | [audit mechanism] |

**AI-ADVISORY components** (human reviews):
| Component | Reviewer | Acceptable because |
|-----------|---------|-------------------|
| [name]    | [role]  | [why advisory is sufficient] |

**DETERMINISTIC components using externally-sourced constants:**
| Component | Constants source | Verified against |
|-----------|-----------------|-----------------|
| [name]    | [publication/package] | [reference + date] |

**Default**: Everything not listed above is DETERMINISTIC with no AI involvement.

After this decision, inform user: "Run /ai-governance audit after build to verify the code matches these boundary decisions."

10. Testing Framework After selection, validate:

• Tests run on all team members' OS (from decision #4)
• CI/CD can test on production-target OS (from decision #5)
• If dev OS ≠ prod OS without containers, CI must test on prod-target OS

11. UI/UX Foundations Keep this lightweight - just enough to guide consistent output:

• Accessibility baseline (default: WCAG AA / Section 508)
• Reference site URL (optional) - "keep styling in this visual family"
• Component library choice (shadcn, MUI, Tailwind defaults, none)
• Color scheme preference (light/dark/system)

Ask me upfront if there are categories to skip or add based on the project.

Recording Decisions

After each decision, append to technology_decisions.md in the project root. Create the file if it doesn't exist.

For each decision, document:

• Decision: [Name] - [Choice]
• Date: [Today's date]
• Options Considered: Brief list with 1-line summaries
• Rationale: Why this choice fits the project
• Key Tradeoffs Accepted: What we're giving up
• Dependencies: How this affects other decisions
• Environment Notes: Any OS-specific or cross-platform considerations (if applicable)

Key Principles

• Understanding over "best practices" - the goal is to learn WHY certain technologies fit certain problems
• No rushing - take time to explain and answer questions
• Project-specific - recommendations should fit the actual constraints (budget, team size, compliance, timeline)
• Honest tradeoffs - every choice has downsides; be clear about them

Getting Started

First action: Create technology_decisions.md in the project root with the initial template (purpose, decision-making philosophy, confirmed constraints section, and decision log header). This ensures the file exists for other commands like /plan-phase that reference it.

Then, if I haven't provided project context above, ask me about:

• What does the application do?
• Who are the users and how many?
• Any compliance or security requirements?
• Budget constraints?
• Will I maintain this myself or with a team?
• Any technologies I already know or want to learn?

---

Phase 2: Implementation Plan Generation

After completing all technology decisions, generate implementation_plan.md in the project root.

Prerequisites: Confirm these files exist before generating the plan:

• requirements.md (from /kickoff)
• design.md (from /kickoff)
• technology_decisions.md (from this command)

Environment check: If local dev OS differs from production OS and containerization wasn't selected, add an environment mismatch risk to the plan.

Implementation Plan Structure:

1. Overview - Brief summary of what will be built and the approach
2. Phase 0: Technology Stack Decisions - Reference to technology_decisions.md (already complete)
3. Phases 1-N - Sequential build phases, each containing:

• Goal: Single sentence describing the phase objective
• Tasks: Numbered list of specific work items
• Deliverable: What's produced when phase is complete

1. Phase Dependencies - Visual or textual representation of which phases depend on others
2. Risk Areas & Mitigation - Known challenges and how to address them
3. Success Criteria - Checklist for determining when the project is complete

Phase Design Principles:

• Each phase should be completable in a focused work session
• Early phases establish foundation (scaffolding, data model, auth)
• Middle phases build core features incrementally
• Later phases handle polish (testing, monitoring, deployment)
• Each phase should produce something testable

After generating the plan, proceed to Phase 2.5.

---

Phase 2.5: Add Maintenance Policy

After generating implementation_plan.md, append a Maintenance section to it.

Purpose: Establish low-overhead dependency and infrastructure maintenance from day one, so the project doesn't accumulate unmanaged tech debt.

Append the following section to implementation_plan.md:

## Maintenance

### Dependency Updates

**Dependabot configuration** — create `.github/dependabot.yml` during Phase 1 (scaffolding):
- Schedule: `monthly` (not daily/weekly — reduces noise for small teams)
- Group all dependencies into a single PR per ecosystem (pip, npm, github-actions)
- Set `open-pull-requests-limit: 5`

**Auto-merge workflow** — create `.github/workflows/dependabot-auto-merge.yml`:
- Auto-merge patch and minor version bumps when CI passes (squash merge)
- Major version bumps require manual review
- Uses `dependabot/fetch-metadata` to detect update type

**Pinning strategy**:
- Use compatible-release pins where possible (`~=3.2` for pip, `^3.2.0` for npm)
- Exact pins only for tools where behavior changes break the build (linters, formatters)

### Quarterly Maintenance Cycle

Pick one day per quarter to:
1. Merge any outstanding grouped Dependabot PR
2. Check for runtime EOL dates (Python, Node) — upgrade if within 6 months of EOL
3. Review infrastructure announcements (hosting platform, database provider)
4. Run full test suite and deploy

**Exception**: Critical/high security advisories — act within 1 week.

### What Doesn't Need Regular Updates

- Infrastructure platforms (Vercel, Neon, etc.) — no action unless breaking change announced
- Runtime versions — annually, or when EOL approaches
- Dev tooling (linters, formatters) — only when they block something

After appending, inform user: "Added maintenance policy to implementation_plan.md. Dependabot and auto-merge files should be created during Phase 1 scaffolding."

Then proceed to Phase 2.75.

---

Phase 2.75: Create naming_conventions.md

After generating implementation_plan.md, create naming_conventions.md in the project root.

Purpose: Establish naming conventions early so Claude Code generates consistent code from Phase 1 onward, and /commit-phase can check compliance.

Seed from technology_decisions.md:

1. Extract toolset-enforced conventions:

• If using Drizzle/Prisma: DB columns = snake_case, TS = camelCase
• If using Zod: API fields = camelCase
• If using React: Components = PascalCase, hooks = use prefix
• If using Playwright/Vitest: Test files = *.test.ts(x)

1. Always include these required patterns:

• data-testid patterns for E2E testing
• Modal callback standards (onClose, onSubmit)
• Error state naming (error, fieldErrors)
• Date/timestamp field naming (Date vs At)

1. Format for Claude Code (not human-readable):

• Use code blocks with exact patterns
• Use tables for quick reference
• Include "NOT" examples for common mistakes

Template structure:

# Naming Conventions

Claude: Read this before generating UI components, API routes, or tests.

## UI Foundations

Accessibility: [WCAG AA / Section 508 baseline]
Reference site: [URL or "none specified"]
Component library: [choice from tech decisions]
Color scheme: [light/dark/system]

## REQUIRED: Test IDs
[code block with data-testid patterns]

## REQUIRED: Modal Props
[TypeScript interface with NOT comments]

## REQUIRED: Error State
[code block with NOT comments]

## Naming Patterns
[table of patterns]

## Toolset-Enforced (No Action Needed)
[table based on tech decisions]

After creating namingconventions.md, inform user: "Created namingconventions.md - Claude Code will reference this when generating code. The /commit-phase skill will check compliance before each phase commit."

Then inform user the next step is /plan-phase 1 to begin detailed planning for the first implementation phase.

---

When to Use

• After /kickoff is complete
• User says "tech stack", "choose technologies", "what stack should I use"
• User says "what technologies should I use", "help me choose a stack", "let's decide on the tech", "what should I build this with"
• Need to make technology decisions for a new project

When NOT to Use

• No requirements.md or design.md yet (use /kickoff first)
• Technology decisions already made
• Ready to start implementing (use /plan-phase)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: takleb3rry
• Source: takleb3rry/claude-global-appbuilding-skills
• License: MIT

Install and usage instructions live in the source repository linked above.