pmagent-cli 0.2.1

Local-first AI project management agent — reads your repo, documents it, watches for changes, builds LLM prompts.

pm-agent

A local-first AI project management agent — reads your repo, documents it, watches for changes, and builds LLM prompts. Runs entirely on your machine. Zero API cost.

---

What it does

pm-agent runs alongside your development workflow. Point it at any repo — new or existing — and it:

• Reads the entire codebase and maps every file, function, and class
• Asks clarifying questions to capture why decisions were made
• Writes a living PROJECT.md — purpose, architecture, code map, decisions, changelog
• Watches for file saves and auto-updates the doc in the background
• Builds context-rich prompts you can paste into any LLM to continue development

No code leaves your machine unless you explicitly configure a cloud provider.

---

Demo

$ python main.py init

── pm-agent init ──────────────────────────────
Indexing repository...        Found 20 files.
Mapping functions and classes... Mapped 16 files, 54 symbols.
Analyzing with LLM...
Running clarifying questions...

1. Why choose Python for this project?
2. What constraints did you face selecting models?
...

Done — .pm/PROJECT.md created

$ python main.py watch

Watching . for changes...
Detected 1 change(s), updating doc...
  + Added JWT token validation in auth.py
  + Updated config.yaml with jwt_secret field

$ python main.py prompt "add rate limiting to the API"

# Project Context — pm-agent
## About This Project ...
## Your Task
add rate limiting to the API
## Instructions ...

---

Installation

git clone https://github.com/Medinz01/pm-agent.git
cd pm-agent
pip install -r requirements.txt

Install and start Ollama, then pull the recommended model:

ollama pull qwen2.5-coder:3b

---

Usage

Initialize a project

# Current directory
python main.py init

# Existing project elsewhere
python main.py init /path/to/your/project

Watch for changes

python main.py watch

Run this in a second terminal while you develop. Every file save triggers an automatic changelog update.

Generate a task prompt

python main.py prompt "add user authentication"
python main.py prompt "find the bug in the payment flow"
python main.py prompt "refactor the database layer"

Copy the output and paste into any LLM — Claude, ChatGPT, Gemini, whatever you have access to.

Add a decision manually

python main.py decision "chose SQLite over PostgreSQL — single user, no concurrency needed"

---

Configuration

Edit config.yaml to switch providers:

# Local (default — free, private)
provider: local
model: qwen2.5-coder:3b
ollama_host: http://localhost:11434

# Groq (free tier — fast, 70B models)
provider: groq
model: llama-3.1-70b-versatile
api_key: your_groq_key

# OpenAI
provider: openai
model: gpt-4o
api_key: your_openai_key

# Anthropic
provider: anthropic
model: claude-sonnet-4-20250514
api_key: your_anthropic_key

---

Supported Providers

Provider	Free?	Recommended model
Ollama (local)	✅ Always free	qwen2.5-coder:3b
Groq	✅ Free tier	llama-3.1-70b-versatile
OpenAI	❌ Paid	gpt-4o
Anthropic	❌ Paid	claude-sonnet-4-20250514

---

Output — .pm/PROJECT.md

# my-project

## Purpose
...

## Code Map
### auth.py
- `generate_token() — Creates a signed JWT for a given user ID`
- `verify_token() — Validates and decodes an incoming JWT`

## Design Decisions
| Question | Decision / Answer | Date |
|---|---|---|
| Why SQLite? | Single user, no concurrency | 2026-03-15 |

## Changelog
### 2026-03-15
- Added JWT token generation in auth.py
- Updated config to include jwt_secret

---

Hardware requirements

Tested on Intel i5 10th gen, 16GB RAM, GTX 1650 4GB VRAM.

Model	VRAM	Speed
qwen2.5-coder:3b	~2GB	Fast
qwen2.5-coder:7b	~4.5GB	Slow (spills to RAM)
Any cloud model	0	Depends on API

---

Project structure

pm-agent/
├── main.py              # CLI entry point
├── config.py            # Load config.yaml
├── indexer.py           # Repo walker + AST code map
├── analyzer.py          # LLM-based repo analysis
├── questioner.py        # Interactive Q&A
├── doc_writer.py        # Read/write PROJECT.md
├── diff_engine.py       # File hash diffing
├── watcher.py           # Watchdog file monitor
├── prompt_builder.py    # Task prompt generator
├── llm/
│   ├── base.py          # Abstract LLM interface
│   ├── factory.py       # Provider selector
│   ├── ollama_client.py
│   ├── openai_client.py
│   └── anthropic_client.py
└── config.yaml

---

Roadmap

• Repo indexing and AST code map
• LLM analysis and Q&A
• Living PROJECT.md doc
• File watcher with auto-changelog
• Task prompt builder
• Multi-provider support (Ollama, OpenAI, Groq, Anthropic)
• Git commit awareness
• pm summary — quick status in terminal
• PyPI package
• VS Code extension

---

License

MIT