Arth Intelligence records every Claude Code session, tool calls, agent spawns, tokens, dollars, on your own machine. Its Experiments page answers the question this guide is about: what does the toolkit actually change, and what does my AI usage cost? This page is the condensed workflow; the full guide has setup, dashboard tour, and privacy details.
Prerequisite: observability enabled via /otel-setup, see Getting Started Step 7. Cost and token data require Claude Code’s native OTEL (CLAUDE_CODE_ENABLE_TELEMETRY=1, which /otel-setup writes); without it the cost columns stay empty.
Every session is auto-tagged with an arth.experiment label, no setup before each launch:
| Mode | Label format |
|---|---|
No-toolkit baseline (plain claude, no plugin) |
auto-baseline-<git-branch>-<first-prompt-slug>-<unix> |
| Toolkit-on session | auto-toolkit-<git-branch>-<unix> |
The zero-config flow:
claude in a project with no plugin).Want telemetry on but toolkit side effects off for the baseline? export OTEL_OBSERVE_ONLY=true before launching. Want a human-readable label instead of the auto one? Set arth.experiment in OTEL_RESOURCE_ATTRIBUTES before launching, your value wins. Auto-tagging can be disabled with ARTH_AUTO_EXPERIMENT_DISABLED=1. Full details: Getting Started 7f.
The comparison fills in side-by-side:
| Metric | What it tells you |
|---|---|
| Cost (USD) | Total spend per run: the bottom line |
| Tokens | Input/output/cache volume behind that cost |
| API calls | How many model round-trips the run took |
| Cache hit rate | How much context was reused instead of re-paid |
| Lines edited | Output volume of actual code change |
| Active time | Wall-clock engagement, not idle time |
Plus workflow attribution, which skills and agents the toolkit-on run used. Two caveats: cost/token/cache metrics need native OTEL (sessions without it show 0), and lines-edited only populates for toolkit-instrumented sessions.
"spike here" drops an amber ◆ on the session’s DAG timeline within ~5s, so you can correlate a cost spike with what you were doing./arth logs export --since 1h or the sidebar’s diagnostic bundle; filter by experiment, marker, session ID, and time range.Measuring tells you what you spent; the Arth Router decides what to spend before the work runs. It routes each task to a model/harness/platform with awareness of the capacity you already paid for, an under-used Max plan window routes to the best models at $0 marginal cost; a burned-down window right-sizes to cheaper ones, governed by budgets and tiers, with every decision explained.
/router-setup, one-command install: discovers
your plan, generates a real pool config, wires the triage hook/router, operate it: summary (override rate +
estimate bias), pools (window burn), calibrate, outcome reporting/arth-setup, set up the whole Arth stack
(intelligence + memory + router) in one command, local (any subset, no
login) or cloud (one SSO sign-in); also switch and uninstallPairs with this guide’s telemetry: the outcomes bridge feeds actual usage back into the router, so its cost estimates are continuously reconciled against what you really spent.