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— Per-harness, from session logs

Analytics that match the bill.

Token volume by model, P50/P95 latency, host load, error breakdown, plan usage. Scoped to assistant, team, or org. Trend windows that compare against the prior period.

Analytics · last 30 days all hosts all assistants
TOKENS · INPUT
14.2M
▲ 18% vs prev 30d
TOKENS · OUTPUT
3.8M
▲ 22%
SESSIONS
412
▼ 6%
SPEND · EST.
$184
▲ $34
P50 LATENCY
1.4s
↔ unchanged

Token spend by day

model: claude-sonnet-4-6 + codex
Sonnet 4.6 Codex

By assistant

last 7d
Kit Bot 2.1M
Archer 1.4M
Madelyn 512K
acme-team 1.1M
Top hosts
macbook-air312 sessions
build-host-0187
tower-server13
Errors
tool: write_file2 perm denied
tool: run_command1 timeout
routine: nightly journalskipped (quiet)
Plan usage
Hosts3 / 4
Seats2 / 2
Teams1 / 5

Numbers that show up before the invoice does

Glueprint already knows what the agent did — analytics is the same data, rolled up. No third-party telemetry; no agent reads exfiltrated to a vendor.

Token spend, model mix, latency

Per-day token volume by model. P50/P95 latency. Estimated spend that survives a Stripe webhook outage. No surprise on the invoice.

Per-assistant and per-team rollups

Drill into a single assistant or pivot to team. The same KPIs, scoped to a smaller surface — easy to spot the routine that's burning tokens.

Host load and session counts

Which host is doing the work, which is idle. Session counts, error rates, and the noisy tools driving them.

Plan usage in one place

Hosts, seats, teams — used vs. limit. Soft enforcement: existing resources keep running on a downgrade; only creation is blocked when over limit.

Errors with context

Tool denials, run_command timeouts, failed approvals. Each row links straight back to the session that caused it.

30 / 60 / 90 day windows

Compare to the previous window. See trends across releases. Filter by host, assistant, team, or model with one click.

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