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/dtannen/pm/gemini-mdgit clone --depth 1 https://github.com/dtannen/pmWrote 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/dtannen/pm/gemini-md)<a href="https://agentmods.dev/instructions/dtannen/pm/gemini-md"><img src="https://agentmods.dev/badge/instructions/dtannen/pm/gemini-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 | $0.01838 | $0.01838 |
| Opus 5 | $0.00919 | $0.00919 |
| Sonnet 5 | $0.00368 | $0.00368 |
| Haiku 4.5 | $0.00184 | $0.00184 |
Grade A, and why
pm GEMINI.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.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gemini Project Analysis: project-manager-mcp
This document provides a summary of the project-manager-mcp project, generated by Gemini.
Project Overview
This project is a sophisticated, Python-based project management system designed for AI-driven software development workflows. It is named project-manager-mcp, where "MCP" stands for Model Context Protocol. The system provides a set of tools, including a web interface and a CLI, to manage development tasks, epics, and projects.
A core feature is its "Response Aware" (RA) methodology, which enables Large Language Models (LLMs) to tag parts of their work where they are uncertain. These "RA tags" allow for targeted human validation, improving the reliability of AI-generated code and content.
Technology Stack
- Backend:
- Framework: FastAPI
- Runtime: Python 3.9+
- Server: Uvicorn (ASGI)
- Real-time Communication: WebSockets for the Model Context Protocol (MCP).
- Database: SQLite (as indicated in the project description).
- CLI: Click
- Data Validation: Pydantic
- Frontend:
- JavaScript: Vanilla JavaScript
- Styling: Standard CSS, organized by component (Kanban, modals, forms).
- Tooling:
- Package Management: Hatchling
- Testing: Pytest (with pytest-asyncio, pytest-cov, pytest-benchmark).
- Code Quality: Black, Ruff, and MyPy for formatting, linting, and static type checking.
- Containerization: Docker (
Dockerfile,docker-compose.yml).
Architecture
The project is a monorepo with a clear src-layout structure.
src/task_manager/: The core Python application package.mcp_server.py: The main FastAPI application, serving the backend API and handling MCP WebSocket connections.cli.py: The entry point for the command-line interface, built with Click.database.py: Manages the SQLite database connection and data access logic.ra_*.py(e.g.,ra_tag_utils.py,ra_instructions.py): Modules dedicated to the "Response Aware" (RA) functionality.static/: Contains the frontend web application assets, including HTML, CSS, and JavaScript for the UI, which features a Kanban board, planning views, and modals.
test/: A comprehensive test suite with unit and integration tests.docs/&ra-docs/: Project and RA-specific documentation.deploy/: Contains Docker and environment configuration for deployment.pyproject.toml: The central configuration file defining dependencies, project metadata, and tool settings.
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.
- 3d ago First seen · 128 lines · 1,838 tokens per session scan A 6ac991f368d8
pm GEMINI.md is an instructions file published in the GitHub repository dtannen/pm (0 stars, last pushed 10mo ago), licensed MIT. It adds 1,838 tokens to every session, about $0.0092 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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