agentcop 0.1.2

Universal forensic auditor for agent systems — OTel-aligned event schema, pluggable violation detectors

Sentinel — The Agent Cop

The cop for agent fleets.

Every agent fleet needs a cop. Agents delegate, handoff, and execute — and without forensic oversight, violations are invisible until they're incidents. agentcop is a universal auditor: ingest events from any agent system, run violation detectors, get structured findings.

OTel-aligned schema. Pluggable detectors. Adapter bridge to your stack. Zero required infrastructure.

pip install agentcop

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How it works

your agent system
      │
      ▼
 SentinelAdapter          ← translate domain events to universal schema
      │
      ▼
  Sentinel.ingest()       ← load SentinelEvents into the auditor
      │
      ▼
  detect_violations()     ← run detectors, get ViolationRecords
      │
      ▼
  report() / your sink    ← stdout, OTel, alerting, whatever

---

Quickstart

from agentcop import Sentinel, SentinelEvent

sentinel = Sentinel()

# Feed it events (any source, any schema — adapt first)
sentinel.ingest([
    SentinelEvent(
        event_id="evt-001",
        event_type="packet_rejected",
        timestamp="2026-03-31T12:00:00Z",
        severity="ERROR",
        body="packet rejected — TTL expired",
        source_system="my-agent",
        attributes={"packet_id": "pkt-abc", "reason": "ttl_expired"},
    )
])

violations = sentinel.detect_violations()
# [ViolationRecord(violation_type='rejected_packet', severity='ERROR', ...)]

sentinel.report()
# [ERROR] rejected_packet — packet rejected — TTL expired
#   packet_id: pkt-abc
#   reason: ttl_expired

Built-in detectors fire on four event types out of the box:

event_type	Detector	Severity
packet_rejected	detect_rejected_packet	ERROR
capability_stale	detect_stale_capability	ERROR
token_overlap_used	detect_overlap_window	WARN
ai_generated_payload	detect_ai_generated_payload	WARN

---

Custom detectors

Detectors are plain functions. Register as many as you need.

from agentcop import Sentinel, SentinelEvent, ViolationRecord
from typing import Optional

def detect_unauthorized_tool(event: SentinelEvent) -> Optional[ViolationRecord]:
    if event.event_type != "tool_call":
        return None
    if event.attributes.get("tool") in {"shell", "fs_write"}:
        return ViolationRecord(
            violation_type="unauthorized_tool",
            severity="CRITICAL",
            source_event_id=event.event_id,
            trace_id=event.trace_id,
            detail={"tool": event.attributes["tool"]},
        )

sentinel = Sentinel()
sentinel.register_detector(detect_unauthorized_tool)

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TrustHandoff adapter

TrustHandoff ships a first-class adapter. If you're using trusthandoff for cryptographic delegation, plug it in directly:

from trusthandoff.sentinel_adapter import TrustHandoffSentinelAdapter
from agentcop import Sentinel

adapter = TrustHandoffSentinelAdapter()
sentinel = Sentinel()

# raw_events: list of dicts from trusthandoff's forensic log
sentinel.ingest(adapter.to_sentinel_event(e) for e in raw_events)

violations = sentinel.detect_violations()
sentinel.report()

The adapter maps trusthandoff's event fields — packet_id, correlation_id, reason, event_type — to the universal SentinelEvent schema. Severity is inferred from event type. Everything else lands in attributes.

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Write your own adapter

Implement the SentinelAdapter protocol to bridge any system:

from agentcop import SentinelAdapter, SentinelEvent
from typing import Dict, Any

class MySystemAdapter:
    source_system = "my-system"

    def to_sentinel_event(self, raw: Dict[str, Any]) -> SentinelEvent:
        return SentinelEvent(
            event_id=raw["id"],
            event_type=raw["type"],
            timestamp=raw["ts"],
            severity=raw.get("level", "INFO"),
            body=raw.get("message", ""),
            source_system=self.source_system,
            trace_id=raw.get("trace_id"),
            attributes=raw.get("metadata", {}),
        )

---

LangGraph integration

Plug into any LangGraph graph with zero changes to your graph code. The adapter reads the debug event stream — node starts, node results, checkpoint saves — and translates each into a SentinelEvent for violation detection.

pip install agentcop[langgraph]

Stream a graph in debug mode and pipe every event through the adapter:

from agentcop import Sentinel
from agentcop.adapters.langgraph import LangGraphSentinelAdapter

adapter = LangGraphSentinelAdapter(thread_id="run-abc")
sentinel = Sentinel()

sentinel.ingest(
    adapter.iter_events(
        graph.stream({"input": "..."}, config, stream_mode="debug")
    )
)

violations = sentinel.detect_violations()
sentinel.report()

Three LangGraph debug event types are translated:

LangGraph event	SentinelEvent type	Severity
task	node_start	INFO
task_result	node_end	INFO
task_result	node_error (if errored)	ERROR
checkpoint	checkpoint_saved	INFO

Each event carries structured attributes — node, task_id, step, triggers, checkpoint_id, next — so you can write targeted violation detectors:

from agentcop import ViolationRecord

def detect_node_failure(event):
    if event.event_type == "node_error":
        return ViolationRecord(
            violation_type="node_execution_failed",
            severity="ERROR",
            source_event_id=event.event_id,
            trace_id=event.trace_id,
            detail={
                "node": event.attributes["node"],
                "error": event.attributes["error"],
            },
        )

sentinel = Sentinel(detectors=[detect_node_failure])

The thread_id passed to LangGraphSentinelAdapter is used as trace_id on every event, correlating all events from a single graph run.

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OpenTelemetry export (optional)

agentcop events use an OTel-aligned schema out of the box (trace_id, span_id, severity levels). To export events as OTel log records:

pip install agentcop[otel]

from agentcop.otel import OtelSentinelExporter
from opentelemetry.sdk._logs import LoggerProvider

exporter = OtelSentinelExporter(logger_provider=LoggerProvider())
exporter.export(events)

Attributes are emitted under the sentinel.* namespace. trace_id and span_id are mapped to OTel trace context.

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Requirements

• Python 3.11+
• pydantic>=2.7

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License

MIT