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AgentAudit

OpenTelemetry GenAI traces → EU AI Act Article 12 evidence reports. We tell you what your traces prove, and what they don't.

What this is

A single-purpose CLI: point it at OpenTelemetry traces from your AI agent, get an HTML evidence report mapped to EU AI Act Article 12.

Deliberately narrow:

  • One framework: EU AI Act Article 12 (seven trace-evidenceable checks)
  • One input: OpenTelemetry GenAI semantic conventions (JSONL)
  • One output: a single self-contained HTML file

Terminal output

Report preview

Quick start

pip install ai-agent-audit

agentaudit report your-traces.jsonl \
  --retention-days 365 \
  --out report.html
open report.html

Already have OTel traces from your own agent (Langfuse, Laminar, OpenLLMetry, plain OTLP exporter)? Point agentaudit report at your JSONL.

From source

git clone https://github.com/lightshadow1/agent-audit.git
cd agent-audit
uv sync --extra dev
uv run agentaudit report tests/fixtures/otel_pass.jsonl \
  --retention-days 365 \
  --out report.html

What gets checked

Seven trace-evidenceable Article 12 requirements:

Check Article Evidenceability
Automatic recording of events 12(1) fully
Session timestamps 12(3)(a) fully
Input recording 12(3)(c) fully
Operational monitoring 12(2)(c) fully
Human oversight markers 14 partially
Log retention policy 26(6) partially
Serious incident reporting 73 partially

fully = trace data alone can prove this. partially = traces give part of the picture; declared config or surrounding context is needed for the rest.

What this is not

Not a compliance score. Article 12 contains sub-requirements that no tracing tool can evidence — risk management documentation, quality management records, technical documentation under Annex IV, component identification under EN 18229-1. The HTML report names those sub-requirements explicitly and points at the artifacts you'd need to evidence them.

Not legal advice. Not a certification. It is auditable evidence for the subset of Article 12 that trace data can demonstrate, with explicit honesty about the subset it cannot.

Three example fixtures

The repo ships three OpenTelemetry trace files that exercise the spectrum of outcomes:

Fixture Origin What it shows
tests/fixtures/otel_pass.jsonl examples/toy_agent.py Well-instrumented agent — every trace-evidenceable check is met
tests/fixtures/otel_under_instrumented.jsonl examples/under_instrumented_agent.py Real agent missing oversight + token tracking — realistic gap pattern
tests/fixtures/otel_fail.jsonl examples/mutate_fixture.py Synthetically broken trace data — decisive failures across most checks

Run any of them through agentaudit report to see how the same logic surfaces different gap shapes.

CLI

agentaudit report <input.jsonl> [options]

Options:
  --source otel              Trace source (only otel in v1)
  --retention-days N         Declared log retention; Article 26(6) requires ≥180
  --out PATH                 HTML report output (default: report.html, '' to skip)
  --json PATH                Optional JSON dump of the full Report object
  --quiet, -q                Suppress the terminal table

Exit codes:
  0  every check is met or not_evidenced
  1  at least one check is not_met (CI gating)
  2  bad input or unsupported source

How it works

  1. Adapt — Read OTLP-JSON (gen_ai.* semantic conventions) into a normalized Span model
  2. Assess — Seven Article 12 checks each return met / partial / not_met / not_evidenced plus evidence and remediation text
  3. Report — Render HTML with status badges, per-check evidence cards, and a prominent "Not trace-evidenceable" section

What traces cannot evidence

Listed in every report:

  • Art. 12(2)(a) — Risk Management System Records
  • Art. 12(2)(b) — Post-Market Monitoring
  • Art. 12(3)(b) — Identification of Natural Persons for Verification
  • EN 18229-1 — Component Identification
  • Art. 11 / Annex IV — Technical Documentation
  • Art. 17 — Quality Management System

Each entry names the artifact you'd need.

Roadmap

v1 covers Article 12 only. Possible v2+ work, gated on real user signal:

  • SOC 2 Common Criteria mappings (same evidence, different labels)
  • NIST AI RMF
  • Multi-agent harness architecture assessment (planner / generator / evaluator)
  • Langfuse REST adapter
  • PDF export

Reference

License

Apache 2.0 — see LICENSE.

Release files for ai-agent-audit 0.1.0

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