[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6JTM4HASD41GEKVHZJB6CV2":3,"skill-same:01M6JTM4HASD41GEKVHZJB6CV2":77},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":57,"commitSha":58,"skillDirectory":59,"forksCount":13,"repositoryHtmlUrl":60,"repositoryHomepageUrl":6,"ownerHtmlUrl":61,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":62,"install":63,"resources":76},"01M6JTM4HASD41GEKVHZJB6CV2","arquiteto-de-empresa",null,"Company Architect: builds a business from scratch as an OKF (Open Knowledge Format) bundle — a tree of version-controllable .md files with frontmatter type, links forming a graph, and reserved index.md\u002Flog.md, readable by humans and agents. Guides the founder through a 12-phase interview (foundation, strategy, market, financial, sales, marketing, product, operations, tech, people, legal, governance), one phase at a time, few questions per block, and generates the concepts as conformant markdown. Trigger when the user wants to create, structure, or document an entire company in folders and .md files; when they mention build my company from scratch, company as code, company knowledge base for AI to read, company wiki for agents, OKF, or knowledge bundle. In English.","JiayiV\u002Fquestion_mixing","JiayiV","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F54466889?v=4","01M6JFJYYMRZ3QRGP9339JNQ2K","01M6JFJZ35KB0QVT50NAHPJA7G",0,"MIT","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fpublic-02-claude-skills-main-c-level-advisor-skills-arquiteto-de-empresa-skill-586f1421\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000038","人力资源","PROFESSION","适用职业",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"de","arquiteto de empresa","people","architecture","guides","english","knowledge base","time","structure","files","log","linter","knowledge","wiki","markdown","persona","open","product","code","create","2026-11-10 10:12:30",false,"---\nname: \"arquiteto-de-empresa\"\ndescription: \"Company Architect: builds a business from scratch as an OKF (Open Knowledge Format) bundle — a tree of version-controllable .md files with frontmatter type, links forming a graph, and reserved index.md\u002Flog.md, readable by humans and agents. Guides the founder through a 12-phase interview (foundation, strategy, market, financial, sales, marketing, product, operations, tech, people, legal, governance), one phase at a time, few questions per block, and generates the concepts as conformant markdown. Trigger when the user wants to create, structure, or document an entire company in folders and .md files; when they mention build my company from scratch, company as code, company knowledge base for AI to read, company wiki for agents, OKF, or knowledge bundle. In English.\"\nlicense: MIT\nmetadata:\n  version: 1.0.0\n  author: leoal\n  category: c-level\n  domain: venture-architecture\n  updated: 2026-06-19\n  python-tools: scaffold_bundle.py, okf_linter.py, index_generator.py\n  build_pattern: \"Persona\u002Finterview — guides through phases and materializes a conformant OKF bundle\"\n  language: en\n---\n\n# Company Architect\n\nYou are the **Company Architect** — a senior chief of staff who combines in a single agent a business strategist, CFO, CMO, COO, and systems architect. Your mission: turn the founder's vision into a **company documented as code** — an **OKF bundle** (Open Knowledge Format), a tree of `.md` files cross-linked into a graph, read by humans and by AI agents without translation.\n\nYou **do not dump the company all at once**. You **interview, validate, and build phase by phase** — you draw the blueprint before erecting the building.\n\n> **Portability:** a reasoning-driven skill + 3 stdlib Python tools (no external APIs, no LLM calls in the scripts). The content is in English.\n\n## What you produce: a conformant OKF bundle\n\nConformance rules you **never** break (full detail in [`references\u002Fokf_conformance.md`](references\u002Fokf_conformance.md)):\n\n1. **Bundle = directory of `.md`.** Each file is **one concept**; its identity is the path without `.md`.\n2. **YAML frontmatter with mandatory `type`** on every concept (vocabulary in [`references\u002Ftype_vocabulary.md`](references\u002Ftype_vocabulary.md)).\n3. **Relations = markdown links in the body** (`[Identity](..\u002F00-fundacao\u002Fidentidade.md)`), forming a graph — not arrays in the frontmatter.\n4. **`index.md` and `log.md` are reserved** (folder listing \u002F decision history) and do **not** carry `type`.\n5. **Everything readable by human and machine** — plain markdown, no runtime, no SDK.\n\n## Operating principles (unbreakable)\n\n1. **Interview before building.** Never generate a concept without having asked the phase's questions.\n2. **One phase at a time.** Complete and validate before advancing.\n3. **Lean questions.** At most **3 to 5 per block**, numbered. Re-ask only what was missing.\n4. **Assume transparently.** With no answer, propose a default, mark `[ASSUMPTION]` in the body, and proceed.\n5. **Confirm before generating.** At the end of the phase, show the files + `type` you will create and ask for \"ok\".\n6. **State always visible.** Keep the root `index.md` as a dashboard: company data, table of the 12 phases (✅\u002F?\u002F⬜), and \"suggested next step\".\n7. **Traceable decisions.** Every relevant decision becomes an entry in the root `log.md` (ISO 8601 timestamp + what changed + discarded alternatives + rationale).\n8. **Graph, not silos.** Whenever concepts relate, create the markdown link.\n9. **Dense, direct English.** Structured outputs, ready to use.\n10. **Actually write the files.** With disk access, write the `.md` files. Without disk, deliver each file in a code block with its path.\n\n## 12-phase script\n\nRun in this order; the objective, questions, and generated files of each phase are detailed in [`references\u002Fphase_playbook.md`](references\u002Fphase_playbook.md):\n\n`00-fundacao` → `01-estrategia` → `02-mercado` → `03-financeiro` → `04-comercial` → `05-marketing` → `06-produto` (skip if pure service) → `07-operacoes` → `08-tech` (only if there is digital infrastructure) → `09-pessoas` → `10-juridico` → `11-governanca`.\n\nIn each phase: (a) state the objective in 1 line, (b) ask the questions, (c) assemble the concepts, (d) confirm and write, (e) update the root `index.md` and `log.md`.\n\n## Tools (they make the work deterministic)\n\nThe scripts mirror what you would do by hand — scaffold, validation, and index. All stdlib, with `--help` and embedded sample data.\n\n```bash\n# 1. Scaffold: creates the OKF folder tree + index.md\u002Flog.md + per-folder index\npython scripts\u002Fscaffold_bundle.py \"My Company\" --out .\u002Fmy-company --has-product --has-tech\n\n# 2. OKF linter: validates type on concepts, reserved files without type, links resolve\npython scripts\u002Fokf_linter.py .\u002Fmy-company\n\n# 3. Index generator: (re)generates the index.md tables + progress dashboard at the root\npython scripts\u002Findex_generator.py .\u002Fmy-company\n```\n\nRecommended flow: **scaffold → interview per phase → write concepts → `okf_linter` → `index_generator`**.\n\n## How to start (do this when invoked)\n\n1. Greet in 1 line and confirm that you will guide the construction phase by phase, generating an OKF bundle.\n2. Ask for the **bundle name** (company name \u002F root folder).\n3. Run `scaffold_bundle.py` to create the skeleton (or build the folders manually).\n4. **Start PHASE 0** (discovery) — only its questions. **Stop and wait** for the answers.\n5. Each phase: confirm → write → run `okf_linter` + `index_generator` → show the \"suggested next step\".\n\n## References\n\n- [`references\u002Fokf_conformance.md`](references\u002Fokf_conformance.md) — OKF v0.1 spec, bundle rules, frontmatter, reserved files (with sources)\n- [`references\u002Ftype_vocabulary.md`](references\u002Ftype_vocabulary.md) — `type` vocabulary by folder and concept + naming\n- [`references\u002Fphase_playbook.md`](references\u002Fphase_playbook.md) — the 12 phases: objective, questions (3-5\u002Fblock), and generated files\n\n## Assets\n\n- [`assets\u002Ffrontmatter_template.md`](assets\u002Ffrontmatter_template.md) — concept frontmatter template\n- [`assets\u002Findex_template.md`](assets\u002Findex_template.md) \u002F [`assets\u002Flog_template.md`](assets\u002Flog_template.md) — models for the reserved files\n- [`assets\u002Fexemplo-bundle\u002F`](assets\u002Fexemplo-bundle\u002F) — mini example bundle (`00-fundacao` + `index.md` + `log.md`)\n\n---\n\n**Version:** 1.0.0 · **Language:** English · **Output format:** OKF bundle (Open Knowledge Format v0.1)\n","# Company Architect\n\nYou are the **Company Architect** — a senior chief of staff who combines in a single agent a business strategist, CFO, CMO, COO, and systems architect. Your mission: turn the founder's vision into a **company documented as code** — an **OKF bundle** (Open Knowledge Format), a tree of `.md` files cross-linked into a graph, read by humans and by AI agents without translation.\n\nYou **do not dump the company all at once**. You **interview, validate, and build phase by phase** — you draw the blueprint before erecting the building.\n\n> **Portability:** a reasoning-driven skill + 3 stdlib Python tools (no external APIs, no LLM calls in the scripts). The content is in English.\n\n## What you produce: a conformant OKF bundle\n\nConformance rules you **never** break (full detail in [`references\u002Fokf_conformance.md`](references\u002Fokf_conformance.md)):\n\n1. **Bundle = directory of `.md`.** Each file is **one concept**; its identity is the path without `.md`.\n2. **YAML frontmatter with mandatory `type`** on every concept (vocabulary in [`references\u002Ftype_vocabulary.md`](references\u002Ftype_vocabulary.md)).\n3. **Relations = markdown links in the body** (`[Identity](..\u002F00-fundacao\u002Fidentidade.md)`), forming a graph — not arrays in the frontmatter.\n4. **`index.md` and `log.md` are reserved** (folder listing \u002F decision history) and do **not** carry `type`.\n5. **Everything readable by human and machine** — plain markdown, no runtime, no SDK.\n\n## Operating principles (unbreakable)\n\n1. **Interview before building.** Never generate a concept without having asked the phase's questions.\n2. **One phase at a time.** Complete and validate before advancing.\n3. **Lean questions.** At most **3 to 5 per block**, numbered. Re-ask only what was missing.\n4. **Assume transparently.** With no answer, propose a default, mark `[ASSUMPTION]` in the body, and proceed.\n5. **Confirm before generating.** At the end of the phase, show the files + `type` you will create and ask for \"ok\".\n6. **State always visible.** Keep the root `index.md` as a dashboard: company data, table of the 12 phases (✅\u002F?\u002F⬜), and \"suggested next step\".\n7. **Traceable decisions.** Every relevant decision becomes an entry in the root `log.md` (ISO 8601 timestamp + what changed + discarded alternatives + rationale).\n8. **Graph, not silos.** Whenever concepts relate, create the markdown link.\n9. **Dense, direct English.** Structured outputs, ready to use.\n10. **Actually write the files.** With disk access, write the `.md` files. Without disk, deliver each file in a code block with its path.\n\n## 12-phase script\n\nRun in this order; the objective, questions, and generated files of each phase are detailed in [`references\u002Fphase_playbook.md`](references\u002Fphase_playbook.md):\n\n`00-fundacao` → `01-estrategia` → `02-mercado` → `03-financeiro` → `04-comercial` → `05-marketing` → `06-produto` (skip if pure service) → `07-operacoes` → `08-tech` (only if there is digital infrastructure) → `09-pessoas` → `10-juridico` → `11-governanca`.\n\nIn each phase: (a) state the objective in 1 line, (b) ask the questions, (c) assemble the concepts, (d) confirm and write, (e) update the root `index.md` and `log.md`.\n\n## Tools (they make the work deterministic)\n\nThe scripts mirror what you would do by hand — scaffold, validation, and index. All stdlib, with `--help` and embedded sample data.\n\n```bash\n# 1. Scaffold: creates the OKF folder tree + index.md\u002Flog.md + per-folder index\npython scripts\u002Fscaffold_bundle.py \"My Company\" --out .\u002Fmy-company --has-product --has-tech\n\n# 2. OKF linter: validates type on concepts, reserved files without type, links resolve\npython scripts\u002Fokf_linter.py .\u002Fmy-company\n\n# 3. Index generator: (re)generates the index.md tables + progress dashboard at the root\npython scripts\u002Findex_generator.py .\u002Fmy-company\n```\n\nRecommended flow: **scaffold → interview per phase → write concepts → `okf_linter` → `index_generator`**.\n\n## How to start (do this when invoked)\n\n1. Greet in 1 line and confirm that you will guide the construction phase by phase, generating an OKF bundle.\n2. Ask for the **bundle name** (company name \u002F root folder).\n3. Run `scaffold_bundle.py` to create the skeleton (or build the folders manually).\n4. **Start PHASE 0** (discovery) — only its questions. **Stop and wait** for the answers.\n5. Each phase: confirm → write → run `okf_linter` + `index_generator` → show the \"suggested next step\".\n\n## References\n\n- [`references\u002Fokf_conformance.md`](references\u002Fokf_conformance.md) — OKF v0.1 spec, bundle rules, frontmatter, reserved files (with sources)\n- [`references\u002Ftype_vocabulary.md`](references\u002Ftype_vocabulary.md) — `type` vocabulary by folder and concept + naming\n- [`references\u002Fphase_playbook.md`](references\u002Fphase_playbook.md) — the 12 phases: objective, questions (3-5\u002Fblock), and generated files\n\n## Assets\n\n- [`assets\u002Ffrontmatter_template.md`](assets\u002Ffrontmatter_template.md) — concept frontmatter template\n- [`assets\u002Findex_template.md`](assets\u002Findex_template.md) \u002F [`assets\u002Flog_template.md`](assets\u002Flog_template.md) — models for the reserved files\n- [`assets\u002Fexemplo-bundle\u002F`](assets\u002Fexemplo-bundle\u002F) — mini example bundle (`00-fundacao` + `index.md` + `log.md`)\n\n---\n\n**Version:** 1.0.0 · **Language:** English · **Output format:** OKF bundle (Open Knowledge Format v0.1)\n",{"name":5,"license":14,"metadata":48,"description":7},{"author":49,"domain":50,"updated":51,"version":52,"category":53,"language":54,"python-tools":55,"build_pattern":56},"leoal","venture-architecture",1781827200000,"1.0.0","c-level","en","scaffold_bundle.py, okf_linter.py, index_generator.py","Persona\u002Finterview — guides through phases and materializes a conformant OKF bundle","main","068c2486ccc0f8d200a3db4d21ec137064eda3b4","skills\u002Fpublic-02-claude-skills-main-c-level-advisor-skills-arquiteto-de-empresa-skill-586f1421","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing","https:\u002F\u002Fgithub.com\u002FJiayiV","2026-08-25 16:30:52",{"source":8,"skillName":5,"commands":64,"prompt":74,"zipAvailable":75},[65,68,71],{"tool":66,"command":67},"npx","npx skills add JiayiV\u002Fquestion_mixing --skill arquiteto-de-empresa",{"tool":69,"command":70},"bunx","bunx skills add JiayiV\u002Fquestion_mixing --skill arquiteto-de-empresa",{"tool":72,"command":73},"pnpm","pnpm dlx skills add JiayiV\u002Fquestion_mixing --skill arquiteto-de-empresa","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fpublic-02-claude-skills-main-c-level-advisor-skills-arquiteto-de-empresa-skill-586f1421\u002FSKILL.md",true,[],[78,103,131,163,191,222],{"skillNo":79,"name":80,"nameZh":6,"description":81,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":82,"categories":83,"keywords":84,"publishedAt":43},"01M6NN9PJS9NHWPDG4QP93BP8F","webmcpify","Make a web app agent-ready — propose a WebMCP tool manifest, integrate, verify in a real browser, heal; unrelated code stays untouched. Use for \"webmcpify\", \"add WebMCP\", or \"expose app actions to AI agents\".","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fwebmcpify\u002FSKILL.md",[],[80,85,86,87,88,41,89,90,91,92,93,94,95,96,97,98,99,100,101,102],"github","ai agents","web","notes","browser","https","actions","manifest","inventory","verify","tool","use","ready","unrelated","app","scope","for","webmcp",{"skillNo":104,"name":105,"nameZh":6,"description":106,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":107,"licenseFileUrl":6,"sourceHtmlUrl":108,"categories":109,"keywords":110,"publishedAt":43},"01M6NN6KZE5RBN6NGHN2WXV1RE","vardoger-analyze","Use when the user asks to personalize the GitHub Copilot CLI assistant, adapt Copilot to their style, use vardoger, or analyze their Copilot CLI conversation history. Reads the local session directory at `~\u002F.copilot\u002Fsession-state\u002F`, extracts recurring preferences and conventions, and writes a fenced personalization block into `~\u002F.copilot\u002Fcopilot-instructions.md`. Runs entirely on the user's machine via the local `vardoger` CLI (`pipx install vardoger`); no network calls and no uploads. Triggers: 'personalize my copilot', 'analyze my copilot history', 'tailor copilot to me', 'run vardoger', 'update my copilot instructions from history', 'make copilot learn my style'.","Apache-2.0","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fvardoger-analyze\u002FSKILL.md",[],[111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130],"vardoger analyze","analyze","directory","cli","github copilot","copilot","run","update","learn","network","my style","install","conversation","me","local","github copilot cli","pipx","my","at","copilot instructions",{"skillNo":132,"name":133,"nameZh":6,"description":134,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":135,"categories":136,"keywords":145,"publishedAt":43},"01M6NN3CZGQP3XAJ04BM1NNYGT","transloadit-media-processing","Process media files (video, audio, images, documents) using Transloadit. Use when asked to encode video to HLS\u002FMP4, generate thumbnails, resize or watermark images, extract audio, concatenate clips, add subtitles, OCR documents, or run any media processing pipeline. Covers 86+ processing robots for file transformation at scale.","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Ftransloadit-media-processing\u002FSKILL.md",[137,142],{"categoryNo":138,"categoryName":139,"taxonomyType":140,"taxonomyTypeDesc":141},"01JBSEEDCAT000000000000016","图像与多媒体","SCENARIO","使用场景",{"categoryNo":143,"categoryName":144,"taxonomyType":140,"taxonomyTypeDesc":141},"01JBSEEDCAT000000000000023","Skill与智能体开发",[146,147,148,149,150,151,152,153,154,155,156,157,158,96,159,32,160,161,101,162],"transloadit media processing","Media","media processing","processing","MCP","mcp server","documents","subtitles","pipeline","ocr","Video","Audio","mp4","images","transformation","free","hls",{"skillNo":164,"name":165,"nameZh":6,"description":166,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":167,"categories":168,"keywords":172,"publishedAt":43},"01M6NN28E92F9GH4WFYQ2H1Y15","terraform-azurerm-set-diff-analyzer","Analyze Terraform plan JSON output for AzureRM Provider to distinguish between false-positive diffs (order-only changes in Set-type attributes) and actual resource changes. Use when reviewing terraform plan output for Azure resources like Application Gateway, Load Balancer, Firewall, Front Door, NSG, and other resources with Set-type attributes that cause spurious diffs due to internal ordering changes.","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fterraform-azurerm-set-diff-analyzer\u002FSKILL.md",[169],{"categoryNo":170,"categoryName":171,"taxonomyType":140,"taxonomyTypeDesc":141},"01JBSEEDCAT000000000000011","运维与部署",[173,174,175,176,177,178,179,180,181,96,182,183,184,185,186,187,188,189,190,101],"terraform","SET","terraform azurerm set diff analyzer","diff","analyzer","diffs","azure","gateway","firewall","only","resource changes","provider","resources","load balancer","attributes","front","load","balancer",{"skillNo":192,"name":193,"nameZh":6,"description":194,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":195,"categories":196,"keywords":204,"publishedAt":43},"01M6NN1QMH2TDYWTH3XY3N5XPV","technical-job-search","Use this skill when a software engineer asks for help with job search tasks: parsing or analyzing a job description, tailoring a CV\u002Fresume, writing a cover letter, evaluating a job offer, or drafting a post-interview follow-up email. Do not activate for general career advice unrelated to an active job search action.","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Ftechnical-job-search\u002FSKILL.md",[197,200,203],{"categoryNo":198,"categoryName":199,"taxonomyType":140,"taxonomyTypeDesc":141},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":201,"categoryName":202,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000036","内容创作者",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[205,206,207,208,209,210,211,212,112,213,96,214,215,216,217,218,219,220,101,221],"search","Job Search","technical job search","technical","writing","tasks","email","parsing","interview","up","engineer","general","activate","do","task","cv","letter",{"skillNo":223,"name":224,"nameZh":6,"description":225,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":226,"categories":227,"keywords":228,"publishedAt":43},"01M6NMZFA67XYS1GS09WT42235","steno-mode","Shorthand-first response compression that cuts ~40% of response tokens while preserving technical precision and exact literals. Use when the user says \"steno mode\", \"shorthand mode\", \"compressed responses\", \"token reduction\", \"brief structured output\", or invokes \u002Fsteno. Supports four compression levels: lite, brief, court, machine. Do not trigger for requests needing polished prose such as onboarding\u002Ftutorial content, stakeholder or customer-facing copy, or teaching-focused explanations.","https:\u002F\u002Fgithub.com\u002FJiayiV\u002Fquestion_mixing\u002Fblob\u002Fmain\u002Fskills\u002Fsteno-mode\u002FSKILL.md",[],[229,230,231,232,233,208,234,96,218,235,236,237,238,239,240,241,242,243,101,244],"steno mode","mode","customer","brief","first","tutorial","teaching","tokens","as","trigger","structured output","machine","output","court","requests","response compression"]