claude-usage AGENTS.md

A repository guide for coding agents that documents the project layout, commands, and architecture. It is written in an `AGENTS.md` file, a convention for giving automated coding tools instructions about a codebase.

In plain words
What is it for?
Use it to understand a small Python project that scans Claude Code usage logs into SQLite and provides terminal reports and a local dashboard.
Why use it?
It gives an agent the project-specific context needed to work consistently without rediscovering basic commands and file roles.

Instructions file for CodexOpenCode

▶ How To Never Run Out Of Codex and Claude Usage Limits AI LABS · about claude-usage AGENTS.md · on YouTube →
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/phuryn/claude-usage/agents-md
Clone the repo
git clone --depth 1 https://github.com/phuryn/claude-usage

Made for: Codex, OpenCode.

Per session 4,058 This file is loaded in full into every session.
When invoked 4,058 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.04058 $0.04058
Opus 5 $0.02029 $0.02029
Sonnet 5 $0.00812 $0.00812
Haiku 4.5 $0.00406 $0.00406

Measured 3d ago against content hash c78d72e54ef4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

claude-usage 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 3d 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.

AGENTS.md · 170 lines

How it starts

The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Guidance for any coding agent (Codex, Claude Code, etc.) working on this repository.

Naming note. This project analyzes Claude Code's local usage logs, so "Claude Code" below always refers to that product (the source of the JSONL data) — not to the agent reading this file. The agent working on the codebase is referred to as "the coding agent" or just "you".

Project shape

Three Python files, stdlib only, no pip install step. Python 3.8+.

  • scanner.py — parses Claude Code JSONL transcripts into a SQLite DB at ~/.claude/usage.db.
  • cli.py — terminal commands (scan / today / week / stats / dashboard).
  • dashboard.py — single-file http.server serving an embedded HTML/JS SPA on localhost:8080.

Use python on Windows, python3 on macOS/Linux. Both work the same.

Common commands

python cli.py scan                  # incremental scan (fast on re-run)
python cli.py today                 # today's usage by model
python cli.py week                  # last 7 days, per-day + by-model
python cli.py stats                 # all-time stats
python cli.py dashboard                          # scan + open http://localhost:8080
python cli.py dashboard --host 0.0.0.0 --port 9000
python cli.py scan --projects-dir PATH           # scan a custom transcripts dir
# or via env vars:
HOST=0.0.0.0 PORT=9000 python cli.py dashboard

python -m unittest discover -s tests -v             # full test suite (CI runs this)
python -m unittest tests.test_scanner -v            # one file
python -m unittest tests.test_scanner.TestProjectNameFromCwd.test_windows_path  # one test

CI (.github/workflows/tests.yml) runs the suite on Python 3.9 / 3.11 / 3.12 against main and PRs.

Architecture

Data flow

~/.claude/projects/**/*.jsonl   →   scanner.parse_jsonl_file()
~/Library/.../Xcode/...                  ↓
                              aggregate_sessions() → upsert_sessions() + insert_turns()
                                         ↓
                              ~/.claude/usage.db (SQLite)
                                         ↓
                  cli.py queries   ←──────────→   dashboard.py /api/data

Read the full file on GitHub · 170 lines

Changes

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.

  1. 3d ago First seen · 170 lines · 4,058 tokens per session scan A c78d72e54ef4

Subscribe to this mod's changes

claude-usage AGENTS.md is an instructions file published in the GitHub repository phuryn/claude-usage (2,185 stars, last pushed 1mo ago), licensed MIT. It adds 4,058 tokens to every session, about $0.0203 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 2026-08-30.

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