Agent Usage is a local usage dashboard for people whose AI agents can hand work to other agents. It makes activity visible by agent, billing domain and model, but it does not estimate a delegation’s impact in advance or automatically switch models to prevent a quota window from running out. The “torch a 5-hour window” wording comes from the project author’s announcement, not from a published exhaustion rate or controlled test.
What the “five-hour window” warning means
Dongsheng’s September 20, 2026 announcement describes a specific risk: an agent that spawns subagents may use capacity in a five-hour window without first estimating the effect or asking for confirmation. The post presents that as the motivation for Agent Usage; it does not quantify how often this happens, report measured exhaustion rates, or establish that every delegated task consumes a quota window in the same way. Read the warning as the author’s concern, not as a benchmark.
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The tool is intended to make usage easier to inspect after or while it accumulates. Its announcement characterizes it as advice rather than an automatic controller: it does not choose a different agent or model for you. The menu-bar app mentioned in the post is roadmap-only, not a shipped feature in that announcement. Read the launch announcement.
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The project’s README describes a macOS-first, local usage center for Codex, Claude Code, OpenCode and Grok. In addition to the announcement’s breakdown by agent, billing domain and model, the README lists provider quota windows and reset times, token and model views, cost information, history, diagnostics and a command-line interface. These are documented project features, not independently verified test results. See the Agent Usage repository.
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Its useful distinction is between signals that describe a provider’s quota and records of activity observed locally. Those can answer different questions: a provider quota reading may show a reported limit or reset time, while local history can show recorded token activity. A usage view can help identify which agent or model is associated with activity, but the dashboard is not evidence that the provider’s quota accounting is exact or that all activity has been captured.
How to interpret the usage and cost figures
The README says the app keeps provider-native quota labels and reset times, while treating local token history as a separate evidence stream. It also distinguishes several kinds of money-related figures rather than treating them as one bill:
- Actual charges: charges recorded as actual, where available.
- Provider estimates: estimated figures attributed to the provider rather than presented as settled charges.
- Subscription fees: fixed plan costs, distinct from per-use calculations.
- API retail equivalents: a comparison value based on API pricing, not the amount charged for a subscription.
The project says unknown models or prices are left unclassified or unpriced instead of being assigned guessed prices or zero values. When reviewing a number, check its label and source: an API-equivalent cost is not a subscription invoice, and local token history is not interchangeable with a provider’s quota report.
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Requirements and installation
According to the repository documentation, installation requires macOS and Node.js 24 or newer. This is the project’s stated requirement, not a claim of independent compatibility testing. The documented global npm installation and launch command are:
npm i -g agent-usage-all-in-one
agent-usageThe README says the local service binds to 127.0.0.1 and stores application data under the user’s local Application Support directory by default. Consult the repository for current setup details and any changes to requirements.
Local data and privacy claims
The project says credentials remain with the clients that own them and usage data stays on the machine. It also says exports omit account identifiers, session IDs, cookies, OAuth tokens and secret values by default. The README describes retaining raw observations for 90 days before compacting them into UTC daily aggregates. These are the project’s stated data-handling practices; they have not been independently security-audited here. Review the repository and your own environment before installing software that reads local usage data.
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Who may find it useful
Agent Usage is most relevant if you use one of its documented coding agents on macOS and want a consolidated view of usage, quota signals, resets and model activity. It may help you notice where activity is concentrated and make your own choices about delegation or model selection. It does not provide the missing pre-run estimate or confirmation gate raised in the announcement, and it should not be treated as a guarantee against exhausting a provider’s allowance.
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