Fullstack development toolkit with project scaffolding for Next.js, FastAPI, MERN, and Django stacks, code quality analysis with security and complexity scoring, and stack selection guidance. Use when the user asks to "scaffold a new project", "create a Next.js app", "set up
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Fullstack development toolkit with project scaffolding for Next.js, FastAPI, MERN, and Django stacks, code quality analysis with security and complexity scoring, and stack selection guidance. Use when the user asks to "scaffold a new project", "create a Next.js app", "set up
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LanguagePython
LicenseMIT
📦 Ships with claude-skills
</> SKILL.md
senior-fullstack.SKILL.md
---name: "senior-fullstack"
description: Fullstack development toolkit with project scaffolding for Next.js, FastAPI, MERN, and Django stacks, code quality analysis with security and complexity scoring, and stack selection guidance. Use when the user asks to "scaffold a new project", "create a Next.js app", "set up FastAPI with React", "analyze code quality", "audit my codebase", "what stack should I use", "generate project boilerplate", or mentions fullstack development, project setup, or tech stack comparison.
---# Senior Fullstack
Fullstack development skill with project scaffolding and code quality analysis tools.
---## Table of Contents
- [Trigger Phrases](#trigger-phrases)
- [Tools](#tools)
- [Workflows](#workflows)
- [Reference Guides](#reference-guides)
---## Trigger Phrases
Use this skill when you hear:
- "scaffold a new project"
- "create a Next.js app"
- "set up FastAPI with React"
- "analyze code quality"
- "check for security issues in codebase"
- "what stack should I use"
- "set up a fullstack project"
- "generate project boilerplate"
---
Deterministic profile picker. Given four assumptions (team-size, cadence, user-facing, budget) plus optional traffic/sensitivity inputs, ranks the four built-in profiles and returns the matched profile with SLO floor and named approver chain. Refuses to recommend a profile without the four required inputs.
The engine encodes the same matrix the conversational grill walks through — use it directly when inputs are already known, or via the `cs-fullstack-engineer` agent for the question-by-question grill.
---
### Project Scaffolder
Generates fullstack project structures with boilerplate code.
- Stack recommendations by use case (MVP, SaaS, Enterprise)
---
## Quick Reference
### Stack Decision Matrix
| Requirement | Recommendation |
|-------------|---------------|
| SEO-critical site | Next.js with SSR |
| Internal dashboard | React + Vite |
| API-first backend | FastAPI or Fastify |
| Enterprise scale | NestJS + PostgreSQL |
| Rapid prototype | Next.js API routes |
| Document-heavy data | MongoDB |
| Complex queries | PostgreSQL |
### Common Issues
| Issue | Solution |
|-------|----------|
| N+1 queries | Use DataLoader or eager loading |
| Slow builds | Check bundle size, lazy load |
| Auth complexity | Use Auth.js or Clerk |
| Type errors | Enable strict mode in tsconfig |
| CORS issues | Configure middleware properly |
---
## Assumptions and Verifiable Success Criteria (Karpathy discipline)
Before this skill scaffolds, recommends, or modifies any code, the following four assumptions MUST be surfaced. If any are unknown, the skill stops and walks the [Forcing-question library](#forcing-question-library-matt-pocock-grill) instead.
**Verifiable success criteria** (Karpathy #4) — every recommendation this skill emits must include three machine-checkable numbers:
- An API latency target (p50, p95, p99 in ms)
- A frontend perf target (LCP, INP, CLS on mobile-4G)
- An uptime / SLO target
If any of those three is not stated, the recommendation is incomplete — go back to Q7 of the forcing-question library.
The `scripts/fullstack_decision_engine.py` tool encodes these checks: it refuses to recommend a profile without all four assumption inputs and prints the verifiable thresholds for the matched profile.
---
## Customization profiles
Four built-in profiles in `profiles/` calibrate every recommendation:
| Profile | When to pick | Cloud ceiling | Pattern |
The tool returns the best-fit profile, the tradeoff against the runner-up (if within 15%), the stack recommendation, the anti-patterns to avoid on that profile, and the named-approver chain. **This tool never auto-approves.**
To add a custom profile: copy `profiles/saas-startup.json` to `profiles/<your-org>.json`, adjust the `constraints` and `stack_recommendations` blocks, and rerun. The JSON is the customization surface — no code changes needed.
---
## Composition map
This skill does NOT reimplement scope owned by the POWERFUL-tier specialists. It forks into them. See `references/composition_map.md` for the full routing table. Key forks:
| Concern | Fork into |
|---|---|
| API contract review | `engineering/skills/api-design-reviewer/` |
The `cs-fullstack-engineer` agent (in `agents/engineering/cs-fullstack-engineer.md`) orchestrates these forks via `context: fork`. Invoke it from another agent with `Agent({subagent_type: "cs-fullstack-engineer", prompt: "..."})` or via the slash command `/cs:fullstack-review <your problem>`.
---
## Forcing-question library (Matt Pocock grill)
Before locking any architecture or stack decision, walk the seven forcing questions in `references/forcing_questions.md`. Each has a recommended answer, canon citation, and kill criterion. The discipline:
1. One question per turn. No bundling.
2. Always recommend the answer with cited canon.
3. Track answers in a working file (e.g., `/tmp/fullstack-grill-<date>.md`).
4. If a kill criterion trips, stop. Do not scaffold around an unresolved gap.
5. After Q7, run `fullstack_decision_engine.py` with the seven answers as inputs.
Summary of the seven questions (full content in the reference):
3. **Direct tool call:** `python scripts/fullstack_decision_engine.py ...` — deterministic profile match without the conversational grill (use when inputs are already known).
See `agents/engineering/cs-fullstack-engineer.md` for the full invocation contract.
