[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6JDMRBP6WRRVC9249KM7VKP":3,"skill-same:01M6JDMRBP6WRRVC9249KM7VKP":75},{"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":27,"publishedAt":48,"linkOnly":49,"markdownContent":50,"markdownBody":51,"frontMatter":52,"refName":53,"commitSha":54,"skillDirectory":55,"forksCount":56,"repositoryHtmlUrl":57,"repositoryHomepageUrl":58,"ownerHtmlUrl":59,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":60,"install":61,"resources":74},"01M6JDMRBP6WRRVC9249KM7VKP","token-budget-advisor",null,"Offers the user an informed choice about how much response depth to consume before answering. Use this skill when the user explicitly wants to control response length, depth, or token budget. TRIGGER when: \"token budget\", \"token count\", \"token usage\", \"token limit\", \"response length\", \"answer depth\", \"short version\", \"brief answer\", \"detailed answer\", \"exhaustive answer\", \"respuesta corta vs larga\", \"cuántos tokens\", \"ahorrar tokens\", \"responde al 50%\", \"dame la versión corta\", \"quiero controlar cuánto usas\", or clear variants where the user is explicitly asking to control answer size or depth. DO NOT TRIGGER when: user has already specified a level in the current session (maintain it), the request is clearly a one-word answer, or \"token\" refers to auth\u002Fsession\u002Fpayment tokens rather than response size.","S3YED\u002Fappie-kit","S3YED","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F62743867?v=4","01M6JBKBRRVP6KMS0VWZ27T3R6","01M6JBKBX0KG30284PW1DBYJT1",14,"MIT","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fecc\u002Ftoken-budget-advisor\u002FSKILL.md",[17,22],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",{"categoryNo":23,"categoryName":24,"taxonomyType":25,"taxonomyTypeDesc":26},"01JBSEEDCAT000000000000040","财务","PROFESSION","适用职业",[28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"token budget advisor","Budget","advisor","token budget","token","maintain","token count","limit","usage","answer","trigger","tokens","auth","do","community","short","choice","Word","how","brief","2026-11-10 10:12:30",false,"---\nname: token-budget-advisor\ndescription: >-\n  Offers the user an informed choice about how much response depth to\n  consume before answering. Use this skill when the user explicitly\n  wants to control response length, depth, or token budget.\n  TRIGGER when: \"token budget\", \"token count\", \"token usage\", \"token limit\",\n  \"response length\", \"answer depth\", \"short version\", \"brief answer\",\n  \"detailed answer\", \"exhaustive answer\", \"respuesta corta vs larga\",\n  \"cuántos tokens\", \"ahorrar tokens\", \"responde al 50%\", \"dame la versión\n  corta\", \"quiero controlar cuánto usas\", or clear variants where the\n  user is explicitly asking to control answer size or depth.\n  DO NOT TRIGGER when: user has already specified a level in the current\n  session (maintain it), the request is clearly a one-word answer, or\n  \"token\" refers to auth\u002Fsession\u002Fpayment tokens rather than response size.\norigin: community\n---\n\n# Token Budget Advisor (TBA)\n\nIntercept the response flow to offer the user a choice about response depth **before** Claude answers.\n\n## When to Use\n\n- User wants to control how long or detailed a response is\n- User mentions tokens, budget, depth, or response length\n- User says \"short version\", \"tldr\", \"brief\", \"al 25%\", \"exhaustive\", etc.\n- Any time the user wants to choose depth\u002Fdetail level upfront\n\n**Do not trigger** when: user already set a level this session (maintain it silently), or the answer is trivially one line.\n\n## How It Works\n\n### Step 1 — Estimate input tokens\n\nUse the repository's canonical context-budget heuristics to estimate the prompt's token count mentally.\n\nUse the same calibration guidance as [context-budget](..\u002Fcontext-budget\u002FSKILL.md):\n\n- prose: `words × 1.3`\n- code-heavy or mixed\u002Fcode blocks: `chars \u002F 4`\n\nFor mixed content, use the dominant content type and keep the estimate heuristic.\n\n### Step 2 — Estimate response size by complexity\n\nClassify the prompt, then apply the multiplier range to get the full response window:\n\n| Complexity   | Multiplier range | Example prompts                                      |\n|--------------|------------------|------------------------------------------------------|\n| Simple       | 3× – 8×          | \"What is X?\", yes\u002Fno, single fact                   |\n| Medium       | 8× – 20×         | \"How does X work?\"                                  |\n| Medium-High  | 10× – 25×        | Code request with context                           |\n| Complex      | 15× – 40×        | Multi-part analysis, comparisons, architecture      |\n| Creative     | 10× – 30×        | Stories, essays, narrative writing                  |\n\nResponse window = `input_tokens × mult_min` to `input_tokens × mult_max` (but don’t exceed your model’s configured output-token limit).\n\n### Step 3 — Present depth options\n\nPresent this block **before** answering, using the actual estimated numbers:\n\n```\nAnalyzing your prompt...\n\nInput: ~[N] tokens  |  Type: [type]  |  Complexity: [level]  |  Language: [lang]\n\nChoose your depth level:\n\n[1] Essential   (25%)  ->  ~[tokens]   Direct answer only, no preamble\n[2] Moderate    (50%)  ->  ~[tokens]   Answer + context + 1 example\n[3] Detailed    (75%)  ->  ~[tokens]   Full answer with alternatives\n[4] Exhaustive (100%)  ->  ~[tokens]   Everything, no limits\n\nWhich level? (1-4 or say \"25% depth\", \"50% depth\", \"75% depth\", \"100% depth\")\n\nPrecision: heuristic estimate ~85-90% accuracy (±15%).\n```\n\nLevel token estimates (within the response window):\n- 25%  → `min + (max - min) × 0.25`\n- 50%  → `min + (max - min) × 0.50`\n- 75%  → `min + (max - min) × 0.75`\n- 100% → `max`\n\n### Step 4 — Respond at the chosen level\n\n| Level            | Target length       | Include                                             | Omit                                              |\n|------------------|---------------------|-----------------------------------------------------|---------------------------------------------------|\n| 25% Essential    | 2-4 sentences max   | Direct answer, key conclusion                       | Context, examples, nuance, alternatives           |\n| 50% Moderate     | 1-3 paragraphs      | Answer + necessary context + 1 example              | Deep analysis, edge cases, references             |\n| 75% Detailed     | Structured response | Multiple examples, pros\u002Fcons, alternatives          | Extreme edge cases, exhaustive references         |\n| 100% Exhaustive  | No restriction      | Everything — full analysis, all code, all perspectives | Nothing                                        |\n\n## Shortcuts — skip the question\n\nIf the user already signals a level, respond at that level immediately without asking:\n\n| What they say                                      | Level |\n|----------------------------------------------------|-------|\n| \"1\" \u002F \"25% depth\" \u002F \"short version\" \u002F \"brief answer\" \u002F \"tldr\"  | 25%   |\n| \"2\" \u002F \"50% depth\" \u002F \"moderate depth\" \u002F \"balanced answer\"        | 50%   |\n| \"3\" \u002F \"75% depth\" \u002F \"detailed answer\" \u002F \"thorough answer\"       | 75%   |\n| \"4\" \u002F \"100% depth\" \u002F \"exhaustive answer\" \u002F \"full deep dive\"     | 100%  |\n\nIf the user set a level earlier in the session, **maintain it silently** for subsequent responses unless they change it.\n\n## Precision note\n\nThis skill uses heuristic estimation — no real tokenizer. Accuracy ~85-90%, variance ±15%. Always show the disclaimer.\n\n## Examples\n\n### Triggers\n\n- \"Give me the short version first.\"\n- \"How many tokens will your answer use?\"\n- \"Respond at 50% depth.\"\n- \"I want the exhaustive answer, not the summary.\"\n- \"Dame la version corta y luego la detallada.\"\n\n### Does Not Trigger\n\n- \"What is a JWT token?\"\n- \"The checkout flow uses a payment token.\"\n- \"Is this normal?\"\n- \"Complete the refactor.\"\n- Follow-up questions after the user already chose a depth for the session\n\n## Source\n\nStandalone skill from [TBA — Token Budget Advisor for Claude Code](https:\u002F\u002Fgithub.com\u002FXabilimon1\u002FToken-Budget-Advisor-Claude-Code-).\nOriginal project also ships a Python estimator script, but this repository keeps the skill self-contained and heuristic-only.\n","# Token Budget Advisor (TBA)\n\nIntercept the response flow to offer the user a choice about response depth **before** Claude answers.\n\n## When to Use\n\n- User wants to control how long or detailed a response is\n- User mentions tokens, budget, depth, or response length\n- User says \"short version\", \"tldr\", \"brief\", \"al 25%\", \"exhaustive\", etc.\n- Any time the user wants to choose depth\u002Fdetail level upfront\n\n**Do not trigger** when: user already set a level this session (maintain it silently), or the answer is trivially one line.\n\n## How It Works\n\n### Step 1 — Estimate input tokens\n\nUse the repository's canonical context-budget heuristics to estimate the prompt's token count mentally.\n\nUse the same calibration guidance as [context-budget](..\u002Fcontext-budget\u002FSKILL.md):\n\n- prose: `words × 1.3`\n- code-heavy or mixed\u002Fcode blocks: `chars \u002F 4`\n\nFor mixed content, use the dominant content type and keep the estimate heuristic.\n\n### Step 2 — Estimate response size by complexity\n\nClassify the prompt, then apply the multiplier range to get the full response window:\n\n| Complexity   | Multiplier range | Example prompts                                      |\n|--------------|------------------|------------------------------------------------------|\n| Simple       | 3× – 8×          | \"What is X?\", yes\u002Fno, single fact                   |\n| Medium       | 8× – 20×         | \"How does X work?\"                                  |\n| Medium-High  | 10× – 25×        | Code request with context                           |\n| Complex      | 15× – 40×        | Multi-part analysis, comparisons, architecture      |\n| Creative     | 10× – 30×        | Stories, essays, narrative writing                  |\n\nResponse window = `input_tokens × mult_min` to `input_tokens × mult_max` (but don’t exceed your model’s configured output-token limit).\n\n### Step 3 — Present depth options\n\nPresent this block **before** answering, using the actual estimated numbers:\n\n```\nAnalyzing your prompt...\n\nInput: ~[N] tokens  |  Type: [type]  |  Complexity: [level]  |  Language: [lang]\n\nChoose your depth level:\n\n[1] Essential   (25%)  ->  ~[tokens]   Direct answer only, no preamble\n[2] Moderate    (50%)  ->  ~[tokens]   Answer + context + 1 example\n[3] Detailed    (75%)  ->  ~[tokens]   Full answer with alternatives\n[4] Exhaustive (100%)  ->  ~[tokens]   Everything, no limits\n\nWhich level? (1-4 or say \"25% depth\", \"50% depth\", \"75% depth\", \"100% depth\")\n\nPrecision: heuristic estimate ~85-90% accuracy (±15%).\n```\n\nLevel token estimates (within the response window):\n- 25%  → `min + (max - min) × 0.25`\n- 50%  → `min + (max - min) × 0.50`\n- 75%  → `min + (max - min) × 0.75`\n- 100% → `max`\n\n### Step 4 — Respond at the chosen level\n\n| Level            | Target length       | Include                                             | Omit                                              |\n|------------------|---------------------|-----------------------------------------------------|---------------------------------------------------|\n| 25% Essential    | 2-4 sentences max   | Direct answer, key conclusion                       | Context, examples, nuance, alternatives           |\n| 50% Moderate     | 1-3 paragraphs      | Answer + necessary context + 1 example              | Deep analysis, edge cases, references             |\n| 75% Detailed     | Structured response | Multiple examples, pros\u002Fcons, alternatives          | Extreme edge cases, exhaustive references         |\n| 100% Exhaustive  | No restriction      | Everything — full analysis, all code, all perspectives | Nothing                                        |\n\n## Shortcuts — skip the question\n\nIf the user already signals a level, respond at that level immediately without asking:\n\n| What they say                                      | Level |\n|----------------------------------------------------|-------|\n| \"1\" \u002F \"25% depth\" \u002F \"short version\" \u002F \"brief answer\" \u002F \"tldr\"  | 25%   |\n| \"2\" \u002F \"50% depth\" \u002F \"moderate depth\" \u002F \"balanced answer\"        | 50%   |\n| \"3\" \u002F \"75% depth\" \u002F \"detailed answer\" \u002F \"thorough answer\"       | 75%   |\n| \"4\" \u002F \"100% depth\" \u002F \"exhaustive answer\" \u002F \"full deep dive\"     | 100%  |\n\nIf the user set a level earlier in the session, **maintain it silently** for subsequent responses unless they change it.\n\n## Precision note\n\nThis skill uses heuristic estimation — no real tokenizer. Accuracy ~85-90%, variance ±15%. Always show the disclaimer.\n\n## Examples\n\n### Triggers\n\n- \"Give me the short version first.\"\n- \"How many tokens will your answer use?\"\n- \"Respond at 50% depth.\"\n- \"I want the exhaustive answer, not the summary.\"\n- \"Dame la version corta y luego la detallada.\"\n\n### Does Not Trigger\n\n- \"What is a JWT token?\"\n- \"The checkout flow uses a payment token.\"\n- \"Is this normal?\"\n- \"Complete the refactor.\"\n- Follow-up questions after the user already chose a depth for the session\n\n## Source\n\nStandalone skill from [TBA — Token Budget Advisor for Claude Code](https:\u002F\u002Fgithub.com\u002FXabilimon1\u002FToken-Budget-Advisor-Claude-Code-).\nOriginal project also ships a Python estimator script, but this repository keeps the skill self-contained and heuristic-only.\n",{"name":5,"origin":42,"description":7},"master","8ec37df6d71fb664ea19d32c079e7d3ff931a8e0","skills\u002Fecc\u002Ftoken-budget-advisor",3,"https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit","https:\u002F\u002Fweblyfe.ai","https:\u002F\u002Fgithub.com\u002FS3YED","2026-08-27 01:54:02",{"source":8,"skillName":5,"commands":62,"prompt":72,"zipAvailable":73},[63,66,69],{"tool":64,"command":65},"npx","npx skills add S3YED\u002Fappie-kit --skill token-budget-advisor",{"tool":67,"command":68},"bunx","bunx skills add S3YED\u002Fappie-kit --skill token-budget-advisor",{"tool":70,"command":71},"pnpm","pnpm dlx skills add S3YED\u002Fappie-kit --skill token-budget-advisor","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fecc\u002Ftoken-budget-advisor\u002FSKILL.md",true,[],[76,108,141,167,197,222],{"skillNo":77,"name":78,"nameZh":6,"description":79,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":80,"categories":81,"keywords":89,"publishedAt":48},"01M6JFD4M6N4DSGC7TXEJ5R3J2","ai-music","AI music generation and audio tools: HeartMuLa lyrics-to-music generation, songwriting craft (+ Suno prompts), and audio spectrogram\u002Ffeature visualization.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fwethlete\u002Fai-music\u002FSKILL.md",[82,85,88],{"categoryNo":83,"categoryName":84,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000013","分析与可视化",{"categoryNo":86,"categoryName":87,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107],"music","ai music","humanizer","visualization","Tools","Audio","hermes","hermes agent","songwriting","suno","lyrics","prompts","heartmula","craft","generation","feature","ai music generation","music generation",{"skillNo":109,"name":110,"nameZh":6,"description":111,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":112,"categories":113,"keywords":120,"publishedAt":48},"01M6JFCZE4XNFQFMNZDHKHT5V5","agentic-webdesign-design-system-ingestion","Use v0 Design Systems 2.0, Bolt Design System Agents, or Lovable to generate production UI from a client's real design system components — not generic Tailwind. Use when building a client website where brand consistency matters.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fweb-design\u002Fagentic-webdesign-design-system-ingestion\u002FSKILL.md",[114,117],{"categoryNo":115,"categoryName":116,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":118,"categoryName":119,"taxonomyType":25,"taxonomyTypeDesc":26},"01JBSEEDCAT000000000000032","设计师",[121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140],"design","agentic","design system","system","ingestion","webdesign","agentic webdesign design system ingestion","components","generate","design systems","website","ui","Tailwind","bolt","lovable","v0","design-system","wed","design system components","appie",{"skillNo":142,"name":143,"nameZh":6,"description":144,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":145,"categories":146,"keywords":149,"publishedAt":48},"01M6JFCVPX3913CFAS6QQJ33ZB","agentic-webdesign-agent-elements","Use 21st.dev Agent Elements — 25 shadcn\u002Fui components purpose-built for AI agent UIs. Tool cards (Bash, Edit, Search, Plan, Subagent, MCP), chat, input, streaming. Open source, shadcn-registry install, no runtime lock-in.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fweb-design\u002Fagentic-webdesign-agent-elements\u002FSKILL.md",[147,148],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":118,"categoryName":119,"taxonomyType":25,"taxonomyTypeDesc":26},[122,150,126,151,152,153,128,154,155,156,157,158,159,160,161,162,163,164,165,166],"elements","agentic webdesign agent elements","MCP","ai agent","registry","search","streaming","open source","open","Bash","plan","subagent","edit","install","input","lock","source",{"skillNo":168,"name":169,"nameZh":6,"description":170,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":171,"categories":172,"keywords":177,"publishedAt":48},"01M6JFCQC7H65M9QJ6TRE71BS1","vercel-deployment","Deploy static sites and frontends to Vercel — handles both CLI and REST API paths, including the CLI token sanitization workaround.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fsoftware-development\u002Fvercel-deployment\u002FSKILL.md",[173,176],{"categoryNo":174,"categoryName":175,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[178,179,180,181,182,183,184,185,186,187,188,189,190,32,191,192,193,194,195,196],"deployment","vercel deployment","vercel","macos","cli","linux","windows","deploy","vercel deploy","REST","api","site","deploy to vercel","rest api","host","sites","paths","sanitization","static site",{"skillNo":198,"name":199,"nameZh":6,"description":200,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":201,"categories":202,"keywords":204,"publishedAt":48},"01M6JFCM4SMTXBM5A01BK2YQG1","software-quality-workflows","Umbrella workflow for TDD, debugging, code simplification, spikes, pre-commit review, and debugger-assisted investigation.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fsoftware-development\u002Fsoftware-quality-workflows\u002FSKILL.md",[203],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221],"workflows","quality","software","software quality workflows","review","tdd","workflow","commit","debugging","code","debugger","pre-commit","investigation","code simplification","user","simplification","for",{"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":235,"publishedAt":48},"01M6JFCGD0M6CEATY01W7YN6DB","react-component-refactoring","Safely refactor large React components into smaller, maintainable pieces using proven patterns","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fsoftware-development\u002Freact-component-refactoring\u002FSKILL.md",[228,231,234],{"categoryNo":229,"categoryName":230,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000007","代码审查",{"categoryNo":232,"categoryName":233,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000009","前端开发",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[236,237,238,239,240,241,242,243,181,244,245,128,246,184,247,214,248,249,250,251],"react","component","refactoring","component refactoring","react component","react component refactoring","frontend","writing","safe","typescript","react components","modular","refactor","simplify","patterns","test-driven-development"]