QA + Agent Triage Pipeline#

This showcase targets maintainers of the host library running QA and AI-assisted triage.

Problem#

You need fast, reproducible diagnosis across many failures while keeping human review as the final decision point.

Pattern#

Run strict diagnostics in CI, export structured bundles, and triage by stable keys (code, signal, fingerprint).

import smonitor

smonitor.configure(
    profile="qa",
    strict_signals=True,
    strict_schema=True,
    event_buffer_size=500,
)

pytest
smonitor export --out smonitor_bundle --max-events 500

Automation pipeline:

  1. CI stores the bundle as an artifact.

  2. Agent inspects triage, normalized, and human_summary.

  3. Triage groups incidents by code + fingerprint.

  4. If needed, compare against a previous bundle.

  5. Agent proposes diagnosis and patch draft.

  6. Maintainer reviews and merges only after tests pass.

Deterministic triage key#

For repeated incidents across runs, use the stable fingerprint already emitted by SMonitor rather than rebuilding your own grouping key downstream.

This avoids brittle grouping by free text while keeping incidents comparable.

Why this works#

  • failures become comparable across runs and environments;

  • triage focuses on stable contracts, not brittle free text;

  • human ownership is preserved.

Where to apply#

  • nightly test pipelines;

  • release-candidate validation;

  • large issue backlogs with repeated incident classes.