Ferramentas de desenvolvimento
headroom
Compress tool outputs, logs and RAG chunks before they reach the LLM — same answers, fewer tokens
★ 74,7 mil estrelasApache-2.0
Ver o guia →toon é um projeto de ferramentas de desenvolvimento de código aberto de toon-format (toon-format/toon no GitHub). Tem 25.476 estrelas no GitHub e 1.123 forks, é publicado sob a licença MIT e foi atualizado pela última vez no GitHub em 8 de outubro de 2026.
TOON: a compact, human-readable serialization of JSON that saves tokens in LLM prompts
Decide what you want to achieve with toon and check the README on GitHub for requirements before installing.
Clone the repository from GitHub (or take the packaged install route in step 3 if the README offers one).
Follow the project's documented install commands — the Run section below lists the exact ones — and add any required API keys or models.
Work through the README's quickstart example end to end, then adapt it to your own project or data.
Benchmarks in the repo compare TOON against JSON on token efficiency across datasets.
Unlike binary formats, TOON stays readable and diffable in an editor.
Encode JSON to TOON for the prompt and decode model output back to JSON with the same tooling.
Use the SDK in code, or the CLI for files and stdin/stdout pipelines (with a --stats flag showing token savings).
The project publishes retrieval accuracy results, not just size claims.
A 'When Not to Use TOON' section honestly covers cases where JSON is the better choice.
Get the TOON source, spec and benchmarks.
git clone https://github.com/toon-format/toon.git
cd toonAdd the SDK to a project, or install the CLI globally.
npm install @toon-format/toon
npm install -g @toon-format/cliConvert a JSON file to TOON and check the token savings with --stats.
npx @toon-format/cli data.json --stats
npx @toon-format/cli input.json -o output.toontoon is maintained by the toon-format organization/account on GitHub, together with open-source contributors, in the public repository toon-format/toon.
Yes — the code is open source under the MIT license. You can use, modify and redistribute it under that license's terms.
No API key — TOON is a free, MIT-licensed format and toolset that runs locally.
JSON is universal but verbose; TOON trades a conversion step for materially fewer tokens on uniform structured data, while staying human-readable.
Clone the repository from GitHub, follow the install commands in the Run section (taken from the project's README), and complete the documented quickstart example before adapting it to your own use case.
Compress tool outputs, logs and RAG chunks before they reach the LLM — same answers, fewer tokens
From ticket to reviewed pull request — an autonomous coding pipeline on your machine.
An AI compute engine: a distributed runtime plus libraries for scaling ML and LLM workloads
Skill Recorder: watch a human do a task once, then generate a reusable AI-agent skill from the recording
See what your coding agents did — and what each task cost in tokens.
Offline AI commit messages from your local LLM.
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Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.