What you’ll build
In ~10 minutes you will:- Instrument a function with
@guarded_action - Produce a local JSONL ledger at
.agent-sentinel/ledger.jsonl - Connect to the Agent Sentinel cloud platform to view telemetry in real-time
Requirements:
- Python 3.9+
- Your agent functions already estimate or know per-call cost (USD) for
cost_usd
Step 1: Install the SDK
Step 2: Instrument an action
On the first guarded call you will see:That is expected here — you have not loaded a policy yet, so nothing is being
enforced and every action is permitted. It is logged once per process, and it
goes away as soon as you configure a policy. See
Policies for budgets, deny lists and rate limits, and
set
PolicyEngine.set_enforcement_mode("fail_closed") in any deployment where
an unconfigured engine should block rather than permit.Step 3: Inspect the local ledger
By default, Agent Sentinel appends JSON Lines to:Step 4: Connect to the cloud platform
1) Sign up for Agent Sentinel
Visit console.agentsentinel.dev and create an account.2) Generate an API key
- Navigate to Settings → API Keys
- Click Generate New Key
- Copy the key immediately (shown only once)
- Store it securely
3) Enable remote sync in your code
4) View telemetry in the web console
- Go to console.agentsentinel.dev
- Navigate to Runs to see your agent execution
- Click into a run to see all actions, costs, and timing
- Explore Interventions, Activity Ledger, and Analytics
Next steps
Set up policies
Configure budget limits, denied actions, and rate limits
Add approvals
Require human approval for sensitive actions
Instrument LLMs
Automatically track OpenAI, Anthropic, Grok, or Gemini calls
Web console guide
Learn all the features of the web console
