AIOS Validation and OpenTelemetry Export

AgenticLens can now validate AI Operations Specification draft artifacts and export structured traces to OTLP/HTTP collectors.

AIOS draft validation

Use validate to run JSON Schema checks against AIOS draft workflow or run artifacts:

agenticlens validate workflow.json --version 0.4
agenticlens validate run.json --version 0.4 --save validation-report.json

Use conformance to run both schema and semantic checks and report draft alignment:

agenticlens conformance run.json --version 0.4
agenticlens conformance run.json --version 0.4 --save conformance-report.json

When the sibling ai-operations-spec repository is not checked out next to agenticlens, pass --spec-root explicitly:

agenticlens conformance run.json \
  --version 0.4 \
  --spec-root ../ai-operations-spec

Conformance output distinguishes AIOS-defined pass/fail issues from AgenticLens-specific rendering. Because AIOS v0.4 is still a draft, the CLI reports draft alignment rather than stable conformance.

OTLP/HTTP trace export

Structured trace() runs can be exported as OTLP/HTTP JSON for tools such as Grafana, Jaeger, or other OTel-compatible collectors.

Configure export directly in code:

from agenticlens import SpanType, trace

with trace(
    "support-agent",
    otlp_endpoint="http://localhost:4318/v1/traces",
    otlp_headers={"Authorization": "Bearer local-dev-token"},
) as recording:
    with recording.span("planner", SpanType.PLANNING) as planner:
        planner.record_tokens(input_tokens=120, output_tokens=30)

You can also configure the endpoint through environment variables:

export AGENTICLENS_OTLP_TRACES_ENDPOINT=http://localhost:4318/v1/traces
export AGENTICLENS_OTLP_HEADERS='Authorization=Bearer local-dev-token'
export AGENTICLENS_OTLP_TIMEOUT_SECONDS=10

After these are set, any configured trace() run exports automatically when the trace context exits.

Local OTLP payload export

If you want to inspect the generated OTLP payload before posting it, use the exporter directly:

from agenticlens import SpanType, trace
from agenticlens.exporters import OTLPTraceExporter

with trace("support-agent") as recording:
    with recording.span("planner", SpanType.PLANNING):
        pass

OTLPTraceExporter().save(recording.run, "run-otlp.json")

See examples/operational_intelligence_demo.py for a runnable example that saves both a run artifact and an OTLP payload, then validates the run with agenticlens conformance.