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 rules/rm2thaddeus/pixel_detective/fastapi-microservice-patternsgit clone --depth 1 https://github.com/rm2thaddeus/Pixel_DetectiveWhat 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 | $0.00000 | $0.03329 |
| Opus 5 | $0.00000 | $0.01665 |
| Sonnet 5 | $0.00000 | $0.00666 |
| Haiku 4.5 | $0.00000 | $0.00333 |
Grade A, and why
fastapi-microservice-patterns 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 — 476 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FastAPI Microservice Development Patterns
🏗️ SERVICE ARCHITECTURE PATTERNS (From Vibe Coding Backend)
Based on proven patterns from ingestion_orchestration_fastapi_app and ml_inference_fastapi_app.
✅ MANDATORY SERVICE STRUCTURE:
1. Application Lifecycle Management
# ✅ ALWAYS use lifespan context manager for startup/shutdown
from contextlib import asynccontextmanager
@asynccontextmanager
async def lifespan(app: FastAPI):
"""Application lifespan manager for startup/shutdown."""
# --- Startup ---
logger.info("Starting up services...")
# Initialize dependencies (database clients, ML models, etc.)
app_state.qdrant_client = QdrantClient(host=qdrant_host, port=qdrant_port)
# Perform health checks and capability probing
_probe_safe_batch_size() # Example from ML service
logger.info("Startup complete.")
yield
# --- Shutdown ---
logger.info("Shutting down services...")
# Cleanup resources
if torch.cuda.is_available():
torch.cuda.empty_cache()
logger.info("Shutdown complete.")
# ✅ Create app with lifespan
app = FastAPI(title="Your Service Name", lifespan=lifespan)
2. Router Organization Pattern
# ✅ ALWAYS organize endpoints in separate router modules
# Structure: /routers/{domain}.py
# backend/{service}/routers/collections.py
router = APIRouter(prefix="/api/v1/collections", tags=["collections"])
# backend/{service}/main.py
from .routers import search, images, collections, ingest
app.include_router(search.router)
app.include_router(images.router)
app.include_router(collections.router)
app.include_router(ingest.router)
3. Dependencies Module Pattern
# ✅ ALWAYS create centralized dependencies.py
# backend/{service}/dependencies.py
class AppState:
"""Centralized application state container."""
def __init__(self):
self.client: SomeClient | None = None
self.config: Dict[str, Any] = {}
app_state = AppState()
def get_client() -> SomeClient:
"""Dependency function to get initialized client."""
if app_state.client is None:
raise RuntimeError("Client has not been initialized.")
return app_state.client
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 · 476 lines · 0 tokens per session scan A b454534f9575
fastapi-microservice-patterns is a cursor rule published in the GitHub repository rm2thaddeus/Pixel_Detective (21 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,329 tokens. 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 2026-08-30.
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