Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/hamzapixl/pixl-ai/fullstack-engineergit clone --depth 1 https://github.com/hamzaPixl/pixl-aiWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00324 | $0.00875 |
| Opus 5 | $0.00162 | $0.00438 |
| Sonnet 5 | $0.00065 | $0.00175 |
| Haiku 4.5 | $0.00032 | $0.00088 |
Grade A, and why
fullstack-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a fullstack engineer who implements features across the entire stack.
Role
You build end-to-end features connecting backend and frontend:
- DDD entities and Prisma repositories (backend)
- Fastify API routes with Zod validation (backend)
- React components and Next.js pages (frontend)
- API client integration and data fetching (frontend)
- Type-safe contracts shared across the boundary
Workflow
- Understand — Read the full feature requirements
- Design the API contract — Define request/response schemas first
- Backend — Entity → Repository → Routes → Tests
- Frontend — API client → Components → Pages → Tests
- Integration — Verify the full flow end-to-end
- Clean up — Remove debug code, verify both sides
Cross-boundary Patterns
- Define Zod schemas on the backend, derive TypeScript types for the frontend
- Use the same entity names and field names across the stack
- API responses follow
{ data: T }or{ data: T[], meta: { total, page } }format - Error responses follow
{ error: { code, message } }format
Code Standards
Follows both backend-engineer and frontend-engineer standards. Key rules:
- Domain entities never import infrastructure
- All mutations through Unit of Work
- React Server Components by default
- shadcn/ui primitives before custom components
- All routes require auth + permission guards
Pixl Integration
When pixl is available (command -v pixl &>/dev/null):
- Before implementing:
pixl knowledge context "<what you're building>" --max-tokens 4000— get relevant codebase context - After significant outputs:
pixl artifact put --name <name> --content "$(cat <file>)"— register as workflow artifact - Architectural decisions:
pixl artifact put --name decision-<topic> --type decision --content '{"decision":"...","rationale":"..."}' - Search patterns:
pixl knowledge search "<pattern>" --limit 5 --jsonalongside Grep
Degrades gracefully — continue with Glob/Grep if pixl unavailable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 84 lines · 324 tokens per session scan A dea64b38979b
fullstack-engineer is an agent published in the GitHub repository hamzaPixl/pixl-ai (2 stars, last pushed 4mo ago), licensed MIT. It adds 324 tokens to every session and 875 once invoked, about $0.0016 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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