head to head · open source
headroom vs prompt-master
headroom has 78,773 GitHub stars, 6,155 forks, 643 open issues and last shipped yesterday. prompt-master has 15,473 stars, 1,791 forks, 33 open issues and last shipped 14 days ago. headroom leads on adoption by 409% (78,773 vs 15,473 stars). headroom is written in Python under Apache-2.0; prompt-master is written in various languages under MIT. headroom has attracted 8% as many forks as stars, prompt-master 12%. headroom was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (llm), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| headroom | prompt-master | |
|---|---|---|
| GitHub stars | ★ 79K | ★ 15K |
| License | Apache-2.0 | MIT |
| Written in | Python | — |
| Last push | 2026-11-04 | 2026-10-22 |
| Forks | ⑂ 6.2K | ⑂ 1.8K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick headroom if
- You weight community size — 79K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick prompt-master if
- You want the prompt-master feature set and don't need the biggest community
- You prefer the MIT license terms
- You evaluated both and prompt-master fits your workflow better
About headroom
Quickstart · Install · Proof · Agents · Docs · Discord · llms.txt AI agents / LLMs: read /llms.txt here, or fetch the live index · full docs blob . Headroom compresses everything your AI agent reads — tool outputs, logs, RAG chunks, files, and conversation history — before it reaches the LLM. Same answers, fraction of the tokens. Compression runs on your machine; no prompt or file content is sent anywhere to be compressed. 10,144 → 1,260 tokens. The same FATAL found. What it does Library — compress(messages) in Python or TypeScript, inline in any app. Proxy — headroom proxy port 8787 , zero code changes, any…
read the full headroom overview →
About prompt-master
A Claude skill that writes the accurate prompts for any AI tool. Zero tokens or credits wasted. Full context and memory retention. No re prompting your way to an answer you should have gotten on attempt one. Works with: Claude, ChatGPT, Codex, Grok, Gemini, o1/o3, MiniMax, Cursor, Claude Code, GitHub Copilot, Windsurf, Bolt, v0, Lovable, Devin, Perplexity, Midjourney, DALL E, Stable Diffusion, ComfyUI, Sora, Runway, ElevenLabs, Zapier, Make, and any AI tool you throw at it. 🚀 Installation RECOMMENDED Claude.ai (browser) 1. Download this repo as a ZIP 2. Go to claude.ai → Sidebar → Customize → Skills → Upload a…
read the full prompt-master overview →
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Frequently asked questions
Is headroom or prompt-master more popular?
headroom has 78,773 GitHub stars and prompt-master has 15,473. headroom has the larger community by that measure.
Are headroom and prompt-master free?
Both are open source. headroom is licensed under Apache-2.0 and prompt-master under MIT. Neither carries a licence fee.
What is the difference between headroom and prompt-master?
headroom is written in Python and prompt-master in various languages. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, headroom or prompt-master?
Choose headroom if you want the larger community (78,773 stars) or its Apache-2.0 licence terms. Choose prompt-master if its feature set, stack or MIT licence fits better. Both are self-hostable.