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RuleDrift

Test whether AI agents retain critical instructions as conversations grow.

Open source Open in the app JSON README (API)

About

Test whether AI agents retain critical instructions as conversations grow.

Details

Kind
MCP servers
Topic
No topic detected
Publisher
ri7in
Origin
official
Category
ferramentas
Transport
local
Version
0.1.1
Stars
1
Open pull requests
5
Last push
2026-09-03T04:05:35Z
Repository state
ativo
Language
TypeScript
License
MIT
Added
2026-08-29 04:01:17
Updated
2026-08-29 04:01:17
Origin id
io.github.ri7in/rule-drift

README

<div align="center">
  <img src="docs/assets/rule-drift-mark.svg" width="88" height="88" alt="RuleDrift logo">
  <h1>RuleDrift</h1>
  <p><strong>Catch the moment your agent drifts from its rules.</strong></p>
</div>

RuleDrift tests whether an AI agent still follows important instructions after a conversation becomes long or distracting.

Run it like a test suite when you change a prompt, model, memory system, or agent workflow. It runs locally and does not sit in front of production requests.

## Quick start

Requires Node.js 22+ and [Ollama](https://ollama.com/).

```bash
ollama pull qwen3:1.7b
npx rule-drift init
npx rule-drift test
```

No paid model API, account, backend, or telemetry is required.

## What you get

- The first conversation point where a rule fails
- Terminal, JSON, and JUnit reports
- Local Ollama and bring-your-own-agent support
- Optional MCP tools for AI coding clients
- Stable exit codes for CI

## MCP

```bash
npx -y rule-drift mcp --root /path/to/your/project
```

See the [MCP setup guide](docs/mcp.md) for client configuration and safety details.

## Documentation

- [Full guide](docs/guide.md)
- [All documentation](docs/README.md)

Contributions are welcome—see [CONTRIBUTING.md](CONTRIBUTING.md). Licensed under [MIT](LICENSE).

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