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description=All-in-one AI framework & toolkit for 10+ AI coding platforms;

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Text of the page (random words):
trellis trellis doc documentation index fetch the complete documentation index at llms txt use this file to discover all available pages before exploring further skip to main content trellis doc home page release english search k changelog tech blog github github search navigation start here trellis github start here trellis install first task how it works commands upgrades tasks specs real world scenarios advanced architecture overview roadmap customizing the workflow custom slash commands custom sub agents custom hooks custom skills custom spec template marketplace configuration multi platform and team configuration appendix a key file paths quick reference appendix b command skill cheat sheet appendix c task json schema reference appendix d jsonl configuration format reference appendix f faq resources acknowledgments use cases open typeless resource marketplace skills spec templates community showcase contributing tech blog changelog on this page what is trellis one line summary comparison with traditional approaches core concepts at a glance why trellis start here trellis openai open in chatgpt all in one ai framework toolkit for 10 ai coding platforms openai open in chatgpt what is trellis ai s capabilities grow like vines full of vitality but spreading everywhere trellis is scaffolding for ai guiding it along the path of your conventions supported platforms claude code cursor opencode codex kiro kilo gemini cli antigravity devin qoder codebuddy github copilot droid pi agent plus any agent that reads the agents skills standard amp cline deep agents firebender kimi code cli warp and more one line summary trellis is training wheels for ai coding assistants it automatically injects your project specs into every ai session so the ai writes code following your standards instead of improvising ai s capabilities grow like vines full of vitality but spreading everywhere trellis is scaffolding for ai guiding it along the path of your conventions comparison with traditional approaches dimension cursorrules claude md skills trellis spec injection method manually loaded each conversation auto loaded but easily truncated user initiated auto injection hooks on capable platforms prelude on others precisely loaded per task spec granularity one large file one large file one per skill modular files composed per task cross session memory none none none workspace journal persistence workflow enforcement none none none auto trigger skills check sub agent verify loop team sharing single user single user shareable but no standard git versioned spec library platform support cursor only claude code only per platform 14 configured platforms shared skill ecosystem core concepts at a glance concept description location spec your coding standards written in markdown ai reads specs before writing code trellis spec workspace each developer s session logs letting ai remember what was done last time trellis workspace task a work unit containing requirements docs and context configuration trellis tasks skill auto triggered workflow modules brainstorm before dev check update spec break loop platform specific skills dir sub agent specialized ai sub process trellis research trellis implement trellis check platform specific agents dir command explicit session entries finish work continue and manual start where needed platform specific commands dir hook auto triggered scripts that inject context at session start sub agent launch etc platforms with hook support claude hooks etc journal session log files recording what was done in each development session trellis workspace name journal n md why trellis feature problem solved auto injection required specs and workflows auto inject into every conversation write once apply forever auto updated spec library best practices live in auto updated spec files the more you use it the better it gets skill first workflow most operations are auto trigger skills ai picks the right one without manual commands team sync share specs across your team one person s best practice benefits everyone session persistence work traces persist in your repo ai remembers project context across sessions quick start install trellis and set up your first project in 5 minutes architecture understand specs tasks hooks and workspaces commands skills reference for slash commands start finish work and auto trigger skills writing specs turn blank templates into executable contracts with trellis update spec install first task i x github powered by this documentation is built and hosted on mintlify a developer documentation platform