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tech-stack
Walk through technology decisions for a new project collaboratively
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
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Walk through technology decisions for a new project collaboratively
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Audit an existing application or guide a new build for AI governance — classifying every function as DETERMINISTIC, AI-ADVISORY, or AI-OPERATIONAL, identifying risk, and recommending hardening. Use when the user asks to "audit AI usage", "check governance", "review where AI is used", "assess AI risk", "governance review", "lock down AI", or when planning a new feature that involves AI and the user wants to understand where AI should vs. shouldn't be used. Also use when the user wants to evaluate whether a component should use AI or deterministic code.
Complete git workflow for a phase - branch, commit, merge, cleanup
Systematic root cause analysis for bugs and failures. Use when something is broken, failing, or behaving unexpectedly — not for quick typos or obvious one-line fixes. Trigger on "diagnose this", "root cause", "why is this broken", "this isn't working", "investigate this error", "what's causing this", "trace this issue". Also use when /execute-phase Layer 1 or Layer 2 fails twice on the same task.
Execute an approved implementation plan, with automated testing, UI verification, and acceptance-criteria review built into every task. Use this skill whenever the user is ready to start building — trigger on phrases like "execute phase X", "implement the plan", "let's start building", "start coding", "build this out", "time to code", "build phase X", "start phase X", "implement phase X", "let's build this", "start the build", "go ahead and build". Also trigger immediately after the user approves output from /plan-phase. Don't wait to be asked explicitly — if a plan exists and the user says something like "looks good, let's go", this is the right skill.
Guide a complex project ideation session through chunk identification, per-chunk discovery, and structured output files ready for /kickoff Pathway A
Deep market research and assumption mapping - second step in the ideation sequence
Basado en la clasificación ocupacional SOC
| name | tech-stack |
| description | Walk through technology decisions for a new project collaboratively |
| argument-hint | ["project-description"] |
Guide me through selecting a technology stack for this project using a collaborative, educational approach.
$ARGUMENTS
For each technology category:
Work through these in order, skipping any that don't apply to this project:
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:
/ vs \) → use path.join() or forward slashes.gitattributes5. Hosting Platform & Deployment Environments First ask: How many environments? Options:
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:
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:
Anti-patterns to flag during this discussion:
verified_against provenanceRecord 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:
11. UI/UX Foundations Keep this lightweight - just enough to guide consistent output:
Ask me upfront if there are categories to skip or add based on the project.
After each decision, append to technology_decisions.md in the project root. Create the file if it doesn't exist.
For each decision, document:
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:
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:
Phase Design Principles:
After generating the plan, proceed to Phase 2.5.
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.
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:
Extract toolset-enforced conventions:
Always include these required patterns:
Format for Claude Code (not human-readable):
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 naming_conventions.md, inform user: "Created naming_conventions.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.
/kickoff is complete/kickoff first)/plan-phase)