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AI InterfacesPlanned

AgentTraceViewer

Timeline of tool calls, reasoning steps and token cost for debugging agent runs.

  • Observability
  • Timeline
  • Tool use
AgentTraceViewer previewAI-03

Illustrative preview of the intended interface.

Overview

What it solves

The problem

Agent runs fail somewhere inside a chain of tool calls, and plain logs hide what the model actually did and why.

The approach

AgentTraceViewer turns a run into a navigable timeline of LLM calls and tool invocations, with inputs, outputs, latency and token cost for every step.

Features

Key features

  • 01

    Span timeline

    A Gantt-style view shows what ran, in what order and for how long.

  • 02

    Nested call tree

    Collapse or expand sub-agents and tool calls to focus on the failing branch.

  • 03

    Payload inspector

    Select any span to read its exact input and output as formatted JSON.

  • 04

    Cost roll-ups

    Token usage and spend summed per span and per run.

Under the hood

How it works

  1. 1

    Capture

    Emit spans from your agent runtime as it executes.

  2. 2

    Normalise

    Map them to one span schema regardless of framework.

  3. 3

    Visualise

    Render the timeline and call tree.

  4. 4

    Inspect

    Select a span to see its payloads, errors and cost.

See it

Demo

Walkthrough video coming soon

A short screen recording will appear here.

Developer experience

Usage

Planned API — this shows the intended developer experience and may change as the component is built.

TracePage.tsx
<AgentTraceViewer
  trace={trace}
  onSelectSpan={(span) => console.log(span.name)}
/>

AI Interfaces

Span schema

The small, framework-neutral shape every trace is converted to.

Span schema
FieldPurpose
nameHuman-readable label, e.g. tool.search_docs.
kindllm, tool or agent — drives colour and grouping.
startMs / endMsPosition and length on the timeline.
input / outputPayloads shown in the inspector.
tokens / costUsdUsage roll-ups per span and per run.

Roadmap

Status & stack

Build progress

  1. Design & API — in progress
  2. Build — not started
  3. Accessibility & performance testing — not started
  4. Demo & write-up — not started

Tech stack

  • React 19
  • TypeScript
  • SVG & CSS timeline
  • OpenTelemetry-style spans

Related research

  • AI Interfaces4 min read

    Building a streaming chat UI that doesn't jank

    Token-by-token rendering, scroll behaviour and abort handling — the patterns that keep an LLM chat feeling instant.

    • Streaming
    • React 19
    • UX
    Read the note

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