[p]rog[mo]: AI-Driven Coding & Developer Efficiency

[p]rog[mo]: Experimental MCP Agent Transforming Coding. Solve complex challenges, boost efficiency, and empower developers with cutting-edge AI-driven solutions.

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38% of users reported increased productivity after just one week

About [p]rog[mo]

What is [p]rog[mo]: AI-Driven Coding & Developer Efficiency?

Imagine having a coding assistant that handles repetitive tasks while you focus on creative problem-solving. That’s [p]rog[mo]—an AI-powered agent that automates knowledge management, code reviews, testing, and documentation. Think of it like a supercharged virtual pair programmer that never sleeps. For example, it can automatically index your project’s technical docs into a vector database so you’ll never waste time hunting down specs again.

How to use [p]rog[mo]: AI-Driven Coding & Developer Efficiency?

Start by installing the Rust-based server as a binary or Docker container. Then configure your project with a .clinefile to guide tasks like code reviews. Want to streamline a messy test suite? Just run progmo test:optimize and watch it auto-generate missing tests while improving coverage. The best part? It can run in "constant mode" to continuously monitor your repo—like having an ever-vigilant code guardian.

[p]rog[mo] Features

Key Features of [p]rog[mo]: AI-Driven Coding & Developer Efficiency?

standout capabilities include:
• **Smart Knowledge Management**: Integrates with Qdrant vector databases to store project context
• **Documentation-Driven Development**: Maintains living docs through an "external brain" system organizing projects, resources, and archives
• **Autonomous Code Reviews**: Creates dedicated branches to suggest improvements while tracking changes in a changelog
• **Test Gardeners**: Not just running tests, but actively pruning outdated ones and boosting coverage

Use cases of [p]rog[mo]: AI-Driven Coding & Developer Efficiency?

Perfect for teams struggling with:
• Keeping sprawling documentation up-to-date (imagine automatically syncing API changes)
• Maintaining test suites in legacy codebases
• Onboarding new developers by auto-generating context-rich issue templates

[p]rog[mo] FAQ

FAQ from [p]rog[mo]: AI-Driven Coding & Developer Efficiency?

**Does it work with other vector databases?**
Currently optimized for Qdrant, but we’re experimenting with Graph RAG approaches using triple stores for richer semantic connections.

**Can it handle large projects?**
Absolutely! The Rust implementation ensures low overhead, even for million-line codebases. We’ve seen teams cut maintenance time by 40%+.

**How customizable is the review process?**
Configure everything from test thresholds to review cadence via YAML files. Need specific linter rules? Just add them to your .clinefile.

Content

[p]rog[mo]

program more

An agent for handling out of band common coding tasks

knowledge management
documentation driven development
code review
test writing and running and gardening

Knowledge Management

p-mo works with a vector datastore to provide specific context to Cline and other mcp clients. It also also for the basic crud operations of tokenizing text sources, uploading them to the vector store and deleting them when no longer needed.

Supported

Qdurant: containerized locally run vector store.

Research

Graph RAG

DDD manager

Starting with the high level "why", manages our critical path and the narrative of our build. Records features and their user stories, technical specification, decisions and everything needed for operating our system. Uses the "external brain" format for knowledge management: projects for planning active efforts (w/ completion horizons), resources for active reference and policy material, archive for archived resources and projects.

Code Review

Using a .codereview file or the .clinefile as a guide (plus any initial prompting), cuts a review branch and iterates over the code, adds tests, runs tests, makes adjustments. Can be run in a constant mode which periodically pulls in latest commits and keeps a change log of review comments and change commits

Test manager

In some ways, more or less the same as "Code Review", but focussed only on running and fixing tests, improving coverage, and changes to the code to improve testing isolation, speed, layering, etc. Can provide "last run" data for a repo's tests.

Implementation

Writing this as a rust server distributed as a binary or container.

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