What Tablif read on Gear: Scikit-learn for RSI's site
Gear: Scikit-learn for RSI describes itself as: “Gear: Scikit-learn for RSI”
- Price model: free tier
- Stage: Live, no waitlist
What it is
Calls itself “framework”.
- Calls itself: framework
“A modular framework for recursive harness evolution.”
What it costs
Has a free plan. Prices quoted: $0.0568, $1.1858.
- Free plan: yes
- Price: $0.0568 · $1.1858
“In a separate cost comparison with both models using the same optimized DSH harness ( a0740800 ), Luna max's API cost averaged $0.0568 per task, versus $1.1858 for Astra max — 95.21% lower .”
“Gear is an open-source framework for recursive self-improvement of AI agent harnesses”
Who it sells to
Sells to developers. Available in 2 languages.
- Sells to: developers
- Languages: English · 简体中文
“Its modular architecture lets developers implement, compare, and extend optimization algorithms.”
“English | 简体中文”
How it runs
A command-line tool. Distributed through the npm. Open source. AI is the core of the product.
- Kind: cli
- Distributed via: npm
- Open source: yes
- AI role: core to the product
“Install rsi-gear@latest and agent-hitch@latest using npm and verify that all required dependencies are available.”
“Gear is an open-source framework for recursive self-improvement of AI agent harnesses (prompts, tools, workflows, and context management).”
What it works with
Names Claude Code, Codex and 5 more on its pages.
- Names: Claude Code · Codex · DSH · +4
“Use Gear through its Refine Skill in Codex, Claude Code, DSH, or another compatible agent environment.”
“Astra + Codex’s 84.1% on AutomationBench’s public Marketing tasks.”
What it offers as proof
Live, no waitlist. Claims “213 stars”. Publishes docs.
- Number claimed: 213 stars
“You must be signed in to star a repository”
“Stars 213 stars”
Sources
Tablif read these pages, last on 28 Oct 2026. Everything above is what the product says about itself; Tablif does not verify every claim.
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