Instrument spans across the loop

The trace tree is the run's skeleton - build it first.

First time here? Paste the Context Pack first so the AI understands your project - open it from the header above.

Prompt Capsule

Add structured tracing to the agent. Span hierarchy: session -> task -> turn -> {model_call, tool_execution, hook_check, compaction, memory_op}. Attributes per span type: model calls get model, tier, tokens in/out, cost, latency, stop reason; tool spans get tool name, argument digest, result size, verdict; hook spans get rule and verdict. Use OpenTelemetry SDK conventions (GenAI semantic conventions where they fit) so exporters and existing backends work. Export to your available backend (an OTLP collector, or a local trace store if self-contained). Add a scrubber on attribute capture: known secret patterns and configured sensitive fields are redacted before export. Verify one session renders as a correct, complete tree.

Paste into EmergentFull Build: complete implementation prompt with explicit requirements

Quick is short. Full Build is recommended for most steps. Strict forces real logic when the AI keeps faking output.

Actual change check

Expected after this step

A complete scrubbed trace tree for a real session.

Should NOT happen

An existing feature broke
A button only logs to console
Data disappears after refresh
Errors fail silently with no visible state

This is what should exist before you continue. If reality does not match, do not move on.

Your notes for this step

Track what changed, failed, or needs follow-up. Notes export with the flow.

Pass the Verify Gate to complete this step

Verify before continuing

Do not move on until every check is true. The complete button stays locked until then.

Hierarchy covers all loop operationsToken/cost attributes on model spansScrubbing verified on a seeded secret

Do not continue if…

! Unstructured print-logging that cannot reconstruct a run
! Traces without token/cost attributes, blinding the economics
! Secrets in span payloads, turning observability into a breach
! Dashboards built, never used - observability without a debugging workflow

If the AI messes this up

Use this when:

- it only made visual forms or placeholder UI
- buttons do nothing or only log to console
- data is not persisted - state disappears on refresh
- something that worked before is now broken

Use this when the AI fakes progress or breaks the feature. It forces a real fix.

The tree has gaps (orphan spans, missing turns). Check context propagation - every operation must open its span inside its parent's context; async boundaries are the usual leak point.