Borrowing it
Nothing to install: this file belongs to raboley/ado-mcp. 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/raboley/ado-mcp/main/CLAUDE.mdgit clone --depth 1 https://github.com/raboley/ado-mcpWrote 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/raboley/ado-mcp/claude-md)<a href="https://agentmods.dev/instructions/raboley/ado-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/raboley/ado-mcp/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80ร15 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/raboley/ado-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/raboley/ado-mcp/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 | $0.01716 | $0.01716 |
| Opus 5.5 | $0.00686 | $0.00686 |
| Sonnet 5.5 | $0.00343 | $0.00343 |
| Haiku 4.5 | $0.00172 | $0.00172 |
Grade A, and why
ado-mcp CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories โ prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency โ measured 2mo 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 โ 143 lines โ stays where its author put it; the contents beside it link to each section on GitHub.
๐ Project Awareness & Context
- Check the
tasks/folder at the start of a new conversation to understand current project requirements, PRDs, and active tasks. - Check CONTRIBUTING.md when working on tasks.
- Use consistent naming conventions, file structure, and architecture patterns as established in the codebase.
- Use venv_linux (the virtual environment) whenever executing Python commands, including for tests.
- Read NEW_TOOL_WORKFLOW.md when asked to create a new tool
๐งฑ Code Structure & Modularity
- Never create a file longer than 500 lines of code. If a file approaches this limit, refactor by splitting it into modules or helper files.
- Organize code into clearly separated modules, grouped by feature or responsibility.
For agents this looks like:
agent.py- Main agent definition and execution logictools.py- Tool functions used by the agentprompts.py- System prompts
- Use clear, consistent imports (prefer relative imports within packages).
- Use clear, consistent imports (prefer relative imports within packages).
- Use python_dotenv and load_env() for environment variables.
- Use logging module to add observability Any errors must include all relevant execution context so an llm can fix it.
๐งช Testing & Reliability
- Always create Pytest end to end tests for new features that a user can experience.
- Only create end to end tests using actual data and real connections - black box test how a user would test.
- ALWAYS use
task testto run tests - never run pytest directly. This ensures proper environment variables are sourced. - Tests run in parallel by default using pytest-xdist for faster execution (~15s vs 80s):
- Use
task testfor parallel execution (default) - Use
task test-sequentialfor debugging when you need sequential execution - Use
task test-single TEST_NAME=path::to::testfor individual test execution
- Use
- Tests require ADO credentials - AZURE_DEVOPS_EXT_PAT and ADO_ORGANIZATION_URL must be set via Taskfile.
- FastMCP converts Pydantic models to dictionaries - tests should expect dictionary responses, not Pydantic objects.
- Dedicated test pipelines are pre-created for pipeline run tests to avoid create/delete overhead.
- After updating any logic, check whether existing unit tests need to be updated. If so, do it. use
task testto ensure everything still works - Tests should live in a
/testsfolder mirroring the main app structure. - Pytest fixture imports: When using pytest fixtures like
telemetry_setup, always import them even if they appear "unused" to linters. The pyproject.toml is configured to allow F401 (unused imports) and F811 (fixture redefinitions) in test files. - NEVER use mocking in tests.
- Include at least:
- 1 test for expected use
- 1 edge case
- 1 failure case
- 1 test to ensure tools and resources are added to the mcp server.
- Include at least:
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.
- 2mo ago First seen ยท 143 lines ยท 1,716 tokens per session scan A dd9563e10021
ado-mcp CLAUDE.md is an instructions file published in the GitHub repository raboley/ado-mcp (0 stars, last pushed 1y ago), licensed MIT. It adds 1,716 tokens to every session, about $0.0069 per session on Opus 5.5. 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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