SkillAgentSearch skills...

Reasonkit

"From Prompt to Cognitive Engineering". — AI: Designed, not Dreamed.

Install / Use

/learn @reasonkit/Reasonkit

README

<div align="center">

ReasonKit

The Reasoning Engine — Auditable Reasoning for Production AI

CI Security Crates.io docs.rs Downloads License Rust

Meta-crate providing unified installation for the complete ReasonKit suite

Documentation | Crates.io | Website

</div>

ReasonKit transforms ad-hoc LLM prompting into structured, auditable reasoning chains. This meta-crate provides a unified installation for the complete ReasonKit suite.

One-Line Install

# Install complete ReasonKit suite
cargo install reasonkit

# Or use the universal installer
curl -fsSL https://get.reasonkit.sh | bash

Installing provides two equivalent binaries:

  • reasonkit — Full command name
  • rk — Short alias for faster typing

What's Included

| Component | Crate | Purpose | | ---------- | --------------------------------------------------------- | ------------------------------------------- | | Core | reasonkit-core | Reasoning engine with ThinkTools | | Memory | reasonkit-mem | Vector storage, hybrid search, RAPTOR trees | | Web | reasonkit-web | Browser automation, MCP sidecar |

Quick Start

CLI Usage

Use reasonkit or the short alias rk — they're identical:

# Run structured reasoning (ThinkTools)
rk think --profile balanced "Should we migrate to microservices?"

# Quick 2-step analysis
rk think --profile quick "Is this email phishing?"

# Maximum rigor (paranoid mode)
rk think --profile paranoid "Validate this cryptographic implementation"

# Verify claims with triangulation
rk verify "GPT-4 has 1.76 trillion parameters"

# Start MCP server for AI agent integration
rk serve

Library Usage

use reasonkit::prelude::*;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    // Create reasoning executor
    let executor = reasonkit::core::thinktool::ProtocolExecutor::new()?;

    // Run GigaThink for multi-perspective analysis
    let result = executor.execute(
        "gigathink",
        reasonkit::core::thinktool::ProtocolInput::query("What factors drive startup success?")
    ).await?;

    println!("Confidence: {:.1}%", result.confidence * 100.0);
    for step in &result.steps {
        println!("- {}", step.as_text().unwrap_or_default());
    }

    Ok(())
}

ThinkTools

Five core reasoning protocols:

| Tool | Shortcut | Purpose | | ----------------- | -------- | ------------------------------------------------ | | GigaThink | gt | Generate 10+ diverse perspectives | | LaserLogic | ll | Precision deductive reasoning, fallacy detection | | BedRock | br | First principles decomposition | | ProofGuard | pg | Multi-source verification (3+ sources) | | BrutalHonesty | bh | Adversarial self-critique |

Profiles

Pre-configured protocol chains:

| Profile | ThinkTools | Confidence | Use Case | | ---------- | ------------------ | ---------- | ------------------ | | quick | GT, LL | 70% | Fast analysis | | balanced | GT, LL, BR, PG | 80% | Standard decisions | | deep | All 5 | 85% | Complex problems | | paranoid | All 5 + validation | 95% | High-stakes |

Features

[dependencies]
# Full suite (default)
reasonkit = "0.1"

# Core reasoning only
reasonkit = { version = "0.1", default-features = false, features = ["core"] }

# Memory layer only
reasonkit = { version = "0.1", default-features = false, features = ["mem"] }

# Web automation only
reasonkit = { version = "0.1", default-features = false, features = ["web"] }

| Feature | Description | | -------- | --------------------------- | | full | All components (default) | | core | Reasoning engine only | | mem | Memory layer only | | web | Web/browser automation only | | python | Python bindings via PyO3 |

LLM Providers

18+ providers supported out of the box:

  • Major Cloud: Anthropic, OpenAI, Google Gemini, Vertex AI, Azure OpenAI, AWS Bedrock
  • Specialized: xAI (Grok), Groq, Mistral, DeepSeek, Cohere, Perplexity
  • Aggregation: OpenRouter (300+ models)
# Set your API key
export ANTHROPIC_API_KEY="sk-ant-..."

# Or use a different provider
rk think --provider openai --model gpt-4o "Your question"

Architecture

reasonkit (meta-crate)
│
├── reasonkit-core    ─── The Reasoning Engine
│   ├── ThinkTools
│   ├── Protocol Executor
│   ├── LLM Client
│   └── MCP Server
│
├── reasonkit-mem     ─── Memory Infrastructure
│   ├── Vector Storage (Qdrant)
│   ├── Sparse Index (Tantivy)
│   ├── Hybrid Retrieval
│   └── RAPTOR Trees
│
└── reasonkit-web     ─── Web Sensing Layer
    ├── Browser Controller
    ├── Content Extraction
    └── MCP Sidecar

Philosophy

"Designed, Not Dreamed" — Structure beats raw intelligence.

ReasonKit imposes systematic reasoning protocols on LLM outputs, producing more reliable, verifiable, and explainable results.

Documentation

  • Website: https://reasonkit.sh
  • API Docs: https://docs.rs/reasonkit
  • Core Docs: https://docs.rs/reasonkit-core
  • Memory Docs: https://docs.rs/reasonkit-mem
  • Web Docs: https://docs.rs/reasonkit-web

Individual Crates

If you only need specific functionality:

# Reasoning only
cargo install reasonkit-core

# Memory layer only
cargo install reasonkit-mem

# Web automation only
cargo install reasonkit-web

License

Apache-2.0 — See LICENSE for details.

Contributing

See CONTRIBUTING.md for guidelines.


Turn Prompts into Protocols | https://reasonkit.sh

View on GitHub
GitHub Stars5
CategoryDevelopment
Updated2d ago
Forks3

Languages

Rust

Security Score

90/100

Audited on Apr 5, 2026

No findings