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.
npx agentmods add instructions/sondt2709/cloud-vm-mcp-py/agents-mdgit clone --depth 1 https://github.com/sondt2709/cloud-vm-mcp-pyWrote 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/sondt2709/cloud-vm-mcp-py/agents-md)<a href="https://agentmods.dev/instructions/sondt2709/cloud-vm-mcp-py/agents-md"><img src="https://agentmods.dev/badge/instructions/sondt2709/cloud-vm-mcp-py/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 | $0.01494 | $0.01494 |
| Opus 5 | $0.00747 | $0.00747 |
| Sonnet 5 | $0.00299 | $0.00299 |
| Haiku 4.5 | $0.00149 | $0.00149 |
Grade A, and why
cloud-vm-mcp-py 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 5d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
MCP server for managing VMs across cloud providers (AWS, Azure). Python 3.10+, uv package manager, FastMCP framework, Pydantic models.
Build & Run
uv sync # Install all dependencies
uv run vm-mcp # Start the MCP server
uv run python cli.py list # CLI: list VMs
Lint, Format, Type Check
uv run ruff check . # Lint (auto-fixes with --fix by default, fix=true in config)
uv run ruff format . # Format
uv run ty check . # Type check (Astral's ty, scoped to vm_mcp/)
Pre-commit hooks run uv-lock sync and ty check automatically.
Tests
uv run pytest tests/ -v # All tests
uv run pytest tests/test_config.py -v # Single file
uv run pytest tests/test_config.py::TestConfigLoader -v # Single class
uv run pytest tests/test_config.py::TestConfigLoader::test_load_valid_config -v # Single test
uv run pytest -k "test_load_valid" -v # By name pattern
uv run pytest tests/ --cov=vm_mcp --cov-report=html # With coverage
Test stack: pytest + pytest-asyncio + pytest-mock. Async tests use @pytest.mark.asyncio.
Tests are class-based (e.g., class TestConfigLoader:). Fixtures in tests/conftest.py.
Project Structure
vm_mcp/
├── __init__.py # Exports main() and mcp
├── __main__.py # python -m vm_mcp entry point
├── config.py # ConfigLoader with file watching (hot-reload, watchdog)
├── mcp.py # FastMCP server, all MCP tool definitions
├── model/
│ ├── credentials.py # AWS/Azure credential Pydantic models
│ └── vm.py # VMState, VMInfo, VMDetails, VMError models
└── providers/
├── base.py # Abstract BaseProvider (ABC)
├── aws.py # AWS EC2 provider
├── azure.py # Azure Compute provider
└── registry.py # Provider factory/lookup
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.
- 5d ago First seen · 163 lines · 1,494 tokens per session scan A fe63a139d8c7
cloud-vm-mcp-py AGENTS.md is an instructions file published in the GitHub repository sondt2709/cloud-vm-mcp-py (0 stars, last pushed 3mo ago), licensed MIT. It adds 1,494 tokens to every session, about $0.0075 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
apm python.instructions.md
Python development guidelines.
technocore-chat AGENTS.md
AGENTS.md instructions for flop-labs/technocore-chat: CI runs exactly these — run them before pushing.
foundry-local python-cffi-pointer-types.instructions.md
Use when working on the Python SDK's native bindings (cffi), especially when defining new Item subclasses, working with flItemQueue, or extending Request/Session methods that pass native handles.
pydantic-ai-gepa AGENTS.md
AGENTS.md instructions for indexedlabs/pydantic-ai-gepa, covering repository guidelines, mighty workflow, project structure & module organization, build, test, and development commands and coding style & naming conventions.
genmedia-izumi-agent GEMINI.md
Gemini CLI instructions for GoogleCloudPlatform/genmedia-izumi-agent.
scitex-python CLAUDE.md
Claude Code instructions for scitex-ai/scitex-python, covering workflow orchestration, 1. plan mode default, 2. subagent strategy, 3. self-improvement loop and 4. verification before done.