Trace UI workbench design

Subject and audience

Subject: a single-session diagnosis trace audit workbench.

Audience: backend and AIOps engineers reviewing an MVP diagnosis run after a demo, incident drill, or regression check.

Single job: turn one trace response into an inspectable ledger that exposes agent flow, evidence, verifier judgement, and skill boundaries without reading raw JSON first.

Frontend approach

Static trace.html, trace.css, and trace.js.
No dependency on a package manager, bundler, external fonts, or remote icons.
Fetches /api/diagnosis/{sessionId}/trace and renders client-side.
Accepts ?sessionId=... and keeps the loaded session id in the URL.

Visual direction

Palette:

#111827 ink rail for the trace frame.
#f7f3ea warm ledger surface.
#1f7a6b evidence green.
#b5472f rejection red.
#c58a19 warning amber.
#5b6472 operational gray.

Type:

UI/body: Inter, ui-sans-serif, system-ui.
Data and labels: ui-monospace, SFMono-Regular, Consolas.

Layout:

+--------------------------------------------------------------------+
| Session id input | Load | status / verdict / counts strip          |
+------------------+----------------------+--------------------------+
| Agent trace rail | Evidence tool ledger | Inspector                |
| ordered steps    | filters + calls      | verifier + RAG + skill   |
+------------------+----------------------+--------------------------+

Signature element: a trace rail that treats each agent step as a ledger entry with ordered markers, duration, token count, and expandable raw model excerpts.

Data mapping

data.session: summary strip, final answer, self-evaluation source.
data.steps: ordered trace rail.
data.toolInvocations: evidence ledger and selected tool inspector.
data.session.selfEvaluation.verifier_evaluation: verdict, groundedness, facts table, and verifier tool_trace_summary.
data.toolInvocations[*].retrievalDetails: RAG query transform, retrieval trace, context pack, rerank trace, and evidence blocks.
steps[*].modelOutput: best-effort extraction of selected_skill.
steps[*].modelInput/modelOutput and tool names: best-effort skill boundary checks for read_skill.

Accessibility and states

Keyboard-focusable controls.
Loading, missing session id, API error, empty steps, empty tools, and missing verifier states.
Responsive three-pane desktop layout that stacks on narrow screens.
Respects prefers-reduced-motion.

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