Borrowing it
Nothing to install: this file belongs to hongshuo-wang/agent-usage-desktop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/hongshuo-wang/agent-usage-desktop/main/AGENTS.mdgit clone --depth 1 https://github.com/hongshuo-wang/agent-usage-desktopWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/hongshuo-wang/agent-usage-desktop/agents-md)<a href="https://agentmods.dev/instructions/hongshuo-wang/agent-usage-desktop/agents-md"><img src="https://agentmods.dev/badge/instructions/hongshuo-wang/agent-usage-desktop/agents-md.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01747 | $0.01747 |
| Opus 5 | $0.00873 | $0.00873 |
| Sonnet 5 | $0.00349 | $0.00349 |
| Haiku 4.5 | $0.00175 | $0.00175 |
Grade A, and why
agent-usage-desktop AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file provides guidance to AI coding agents when working with code in this repository.
Build & Run
Desktop app (Tauri)
npm install # install frontend deps
npx tauri dev # dev mode (hot-reload frontend + Rust)
npx tauri build # production build → .app/.dmg/.msi/.deb
Before tauri build, place the Go sidecar binary in src-tauri/binaries/:
# macOS arm64 example:
CGO_ENABLED=0 GOOS=darwin GOARCH=arm64 \
go build -o src-tauri/binaries/agent-usage-aarch64-apple-darwin .
# macOS x86_64:
CGO_ENABLED=0 GOOS=darwin GOARCH=amd64 \
go build -o src-tauri/binaries/agent-usage-x86_64-apple-darwin .
# Linux:
CGO_ENABLED=0 GOOS=linux GOARCH=amd64 \
go build -o src-tauri/binaries/agent-usage-x86_64-unknown-linux-gnu .
# Windows:
CGO_ENABLED=0 GOOS=windows GOARCH=amd64 \
go build -o src-tauri/binaries/agent-usage-x86_64-pc-windows-msvc.exe .
Binary naming must match Tauri's externalBin convention: agent-usage-{rust-target-triple}[.exe].
Go backend (standalone, for development)
go build -o agent-usage-desktop . # build binary
./agent-usage-desktop # run (reads config.yaml by default)
./agent-usage-desktop --config path/to/config.yaml
./agent-usage-desktop --port 9800 # override server port
./agent-usage-desktop version # print version info
Testing
go test ./... # all tests
go test ./internal/collector/... # single package
go test ./internal/storage/... -run TestDedup # single test
No CGO required — the SQLite driver (modernc.org/sqlite) is pure Go.
Architecture
Single-binary Go application that collects AI coding agent token usage from local JSONL session files, stores it in SQLite, and serves a REST API. Also ships as a Tauri v2 desktop app wrapping the same Go backend as a sidecar process.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 116 lines · 1,747 tokens per session scan A 4e39801488af
agent-usage-desktop AGENTS.md is an instructions file published in the GitHub repository hongshuo-wang/agent-usage-desktop (4 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 1,747 tokens to every session, about $0.0087 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
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vscode buildNext.instructions.md
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langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.