Borrowing it
Nothing to install: this file belongs to Monadical-SAS/cubbi. 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/Monadical-SAS/cubbi/main/CLAUDE.mdgit clone --depth 1 https://github.com/Monadical-SAS/cubbiWrote 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/monadical-sas/cubbi/claude-md)<a href="https://agentmods.dev/instructions/monadical-sas/cubbi/claude-md"><img src="https://agentmods.dev/badge/instructions/monadical-sas/cubbi/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/monadical-sas/cubbi/claude-md"><img src="https://agentmods.dev/badge/instructions/monadical-sas/cubbi/claude-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00581 | $0.00581 |
| Opus 5 | $0.00291 | $0.00291 |
| Sonnet 5 | $0.00116 | $0.00116 |
| Haiku 4.5 | $0.00058 | $0.00058 |
Grade A, and why
cubbi CLAUDE.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 9d 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cubbi Container Development Guide
Build Commands
# Install dependencies using uv (Astral)
uv sync
# Run Cubbi CLI
uv run -m cubbi.cli
Lint/Test Commands
# Run linting
uvx ruff check .
# Run type checking (note: currently has unresolved stub dependencies)
# Skip for now during development
# uv run --with=mypy mypy .
# Run formatting
uvx ruff format .
# Run all tests
uv run -m pytest
# Run a specific test
uv run -m pytest tests/path/to/test_file.py::test_function
## Dependencies management
DO not use pip.
Use uv instead:
- Add a dep: uv add <dep>
- Remove a dep: uv remove <dep>
- Update deps: uv sync
Code Style Guidelines
- Imports: Group standard library, third-party, and local imports with a blank line between groups
- Formatting: Use Ruff with 88 character line length
- Types: Use type annotations everywhere; import types from typing module
- Naming: Use snake_case for variables/functions, PascalCase for classes, UPPER_CASE for constants
- Error Handling: Use specific exceptions with meaningful error messages
- Documentation: Use docstrings for all public functions, classes, and methods
- Logging: Use the structured logging module; avoid print statements
- Async: Use async/await for non-blocking operations, especially in FastAPI endpoints
- Configuration: Use environment variables with YAML for configuration
Refer to SPECIFICATIONS.md for detailed architecture and implementation guidance.
Cubbi images
A cubbi image is a flavored docker image that wrap a tool (let's say goose), and dynamically configure the tool when the image is starting. All cubbi images are defined in cubbi/images directory.
Each image must have (let's take goose image for example):
goose/cubbi_image.yaml, list of persistent paths, etc.goose/Dockerfile, that is used to build the cubbi image with cubbi toolsgoose/goose_plugin.py, a plugin file named of the cubbi image name, that is specific for this image, with the intent to configure dynamically the docker image when starting with the preferences of the user (via environment variable). They all importcubbi_init.py, but this file is shared accross all images, so it is normal that execution of the plugin import does not work, because the build system will copy the file in place during the build.goose/README.md, a tiny readme about the image
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.
- 9d ago First seen · 63 lines · 581 tokens per session scan A 0ffe2d310f34
cubbi CLAUDE.md is an instructions file published in the GitHub repository Monadical-SAS/cubbi (10 stars, last pushed 7mo ago), licensed MIT. It adds 581 tokens to every session, about $0.0029 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.
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