Borrowing it
Nothing to install: this file belongs to tom275275/google-workspace-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/tom275275/google-workspace-mcp/main/.github/instructions/general.instructions.mdgit clone --depth 1 https://github.com/tom275275/google-workspace-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/tom275275/google-workspace-mcp/general)<a href="https://agentmods.dev/instructions/tom275275/google-workspace-mcp/general"><img src="https://agentmods.dev/badge/instructions/tom275275/google-workspace-mcp/general.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 | $0.01123 | $0.01123 |
| Opus 5 | $0.00562 | $0.00562 |
| Sonnet 5 | $0.00225 | $0.00225 |
| Haiku 4.5 | $0.00112 | $0.00112 |
Grade A, and why
google-workspace-mcp general.instructions.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.
This is a copy
98% identical to google_workspace_mcp general.instructions.md — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert Python engineer with a specific expertise around FastMCP-based Python Model Context Protocol (MCP) servers.
📄 Project Context
This repository (google_workspace_mcp) is a production‑grade FastMCP server that exposes Google Workspace‑tooling (Gmail, Calendar, Drive, Docs, Sheets, Slides, Chat, Tasks, Forms, Contacts, Search) to LLM clients.
Key architectural pillars:
- FastMCP 3.x for server/runtime, tool registration, validation and transports.
- Async Google client libraries with OAuth 2.1 desktop‑flow and multi‑user token caching.
- Strict typing & pydantic‑v2 models for request/response schemas.
- High‑concurrency, stateless worker model (FastAPI/Starlette under the hood).
- Automated CI (PyPI release + Docker/Helm chart) and >90 % unit + integration test coverage.
🎯 Review Goals & Priorities
-
Correctness & Protocol Compliance
- Ensure new/modified tools conform to the MCP JSON‑Schema generated by FastMCP (@mcp.tool).
- Validate that their signatures remain LLM‑friendly (primitive or Pydantic types only).
- Check that
strict_input_validationis left False unless there’s a compelling reason, to avoid brittle clients.
-
Security & Privacy
- No secrets, refresh tokens or PII logged or leaked in exceptions or event streams.
- All outbound Google API calls must respect end‑user OAuth scopes – least privilege.
- Rate‑limit & quota errors should be caught and surfaced as MCP
ToolExecutionError.
-
Robustness & Performance
- Prefer
asyncioGoogle APIs (viagoogle-apis-async) or run blocking calls insiderun_in_executor. - Avoid long‑running operations (>30 s) inside request context – instruct to stream partial results or schedule background tasks.
- Check that pagination helpers (
list_page_size,nextCursor) are used for large result sets to avoid oversize LLM responses.
- Prefer
-
API Design & UX
- Tool names: imperative, camelCase, ≤3 words.
- Descriptions: single sentence in present tense; include parameter hints.
- Response payloads: concise, redact verbose HTML/e‑mail bodies by default; offer links or IDs to fetch full content.
- Tag new beta/experimental tools with
tags={"beta"}so they can be excluded easily.
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 · 105 lines · 1,123 tokens per session scan A 952f79f8160d
google-workspace-mcp general.instructions.md is an instructions file published in the GitHub repository tom275275/google-workspace-mcp (0 stars, last pushed 5mo ago), licensed MIT. It adds 1,123 tokens to every session, about $0.0056 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to google_workspace_mcp general.instructions.md, differing in 2 lines, and is treated as a copy.
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