AgentStackPro Cookbook

We just dropped 26 end-to-end recipes showing how to integrate every AgentStackPro feature into your LangGraph agents.

Python & TypeScript. Every recipe is a complete, runnable example — not a snippet.

What's inside:

🔍 Tracing & Observability — Full span-level tracing with structured logging

🛡️ Guardrails — Input/output validation with PII scanning baked in

⚡ Response Caching — Semantic deduplication to cut costs by 40%+

🔐 Policy Gates & HITL Approvals — Enforce action-level access control with human-in-the-loop

📊 Decision Audit Trails — Every agent decision logged with reasoning, confidence scores, and alternatives

🧪 Evaluations & Experiments — Dataset-driven testing with automated scoring

🔄 Sessions, State & Versioning — Persistent conversations, checkpointed state, rollback-ready configs

📈 Usage Analytics & Cost Tracking — Token-level budgets with threshold alerts

🐕 Trace Watchdog — Anomaly detection for latency spikes, error bursts, and token explosions

✅ Formal Verification — Constraint-based validation before actions execute

🏛️ Governance Reports — Automated compliance reporting for EU AI Act readiness

Every recipe follows a battle-tested pattern: ✅ Pydantic/Zod strict validation ✅ Structured error handling with fallbacks ✅ build_graph() → run_demo() → __main__ runner ✅ Real LLM calls (swap in your provider) ✅ Production comments marking customization points

No pip install. No npm package. Download the SDK from your dashboard, drop it in your project, and start with Recipe 1.

Each recipe builds on patterns from the previous one.

👉 Try it now: https://agentstackpro.dev/cookbook