[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71JJMTCGHAZB68HJCMTV1W6":3,"skill-same:01M71JJMTCGHAZB68HJCMTV1W6":86},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":31,"commitSha":66,"skillDirectory":5,"forksCount":14,"repositoryHtmlUrl":67,"repositoryHomepageUrl":6,"ownerHtmlUrl":68,"ownerBlogUrl":69,"ownerDescription":70,"updatedAt":71,"install":72,"resources":85},"01M71JJMTCGHAZB68HJCMTV1W6","tokenwise",null,"Measurement-driven model router for Claude Code. Routes Haiku\u002FSonnet\u002FOpus per task class, logs every routed task with real $ numbers, and A\u002FB tests cheaper tiers before you trust the savings.","agency-black\u002FSkills","agency-black","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F234862658?v=4","01M6HWVFPNGNR5N2CX9ECSAD57","agencia.black","01M719WF77BF3HN0N9FK1APEFY",0,"MIT","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Ftokenwise\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[5,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"license","router","task","logs","code","you","critical","main","token-optimization","tests","testing","Optimization","for","model","model router","developer-tools","trust","community","measurement","2026-11-10 10:12:30",false,"---\nname: tokenwise\ndescription: \"Measurement-driven model router for Claude Code. Routes Haiku\u002FSonnet\u002FOpus per task class, logs every routed task with real $ numbers, and A\u002FB tests cheaper tiers before you trust the savings.\"\ncategory: developer-tools\nrisk: critical\nsource: community\nsource_repo: CodeShuX\u002Ftokenwise\nsource_type: community\ndate_added: \"2026-05-12\"\nauthor: CodeShuX\ntags: [model-routing, token-optimization, cost-reduction, anthropic, haiku, sonnet, opus, claude-code, ab-testing, measurement]\ntools: [claude]\nlicense: \"MIT\"\nlicense_source: \"https:\u002F\u002Fgithub.com\u002FCodeShuX\u002Ftokenwise\u002Fblob\u002Fmain\u002FLICENSE\"\nplugin:\n  targets:\n    codex: blocked\n    claude: blocked\n---\n\n# TokenWise — Measurement-Driven Model Router\n\n## Overview\n\nA Claude Code skill that auto-routes subtasks to the cheapest model that can handle them (Haiku for grunt work, Sonnet for scoped reasoning, Opus only for synthesis), then logs every routed task to a local NDJSON with real token + cost numbers. Includes an A\u002FB test subcommand that runs the same task across multiple tiers and scores quality, so the routing decisions are verified against the user's real workload — not estimated.\n\nAnthropic's own bug tracker (Issue #27665) reports 93.8% of Max-subscriber Claude Code tokens flow to Opus. Existing routers (claude-router, wshobson, VoltAgent) either pin models statically or route by vibes-based heuristics with no measurement. TokenWise fills the measurement gap.\n\n## When to use\n\n- Cutting Claude Code token spend without sacrificing output quality\n- Validating whether Haiku\u002FSonnet is \"good enough\" for a specific task class before trusting auto-routing\n- Auditing where Opus tokens are actually being burned\n- Logging per-session cost data for finance or chargeback\n\n## Subcommands\n\n- `\u002Ftokenwise:install` — guided installer with diff preview, automatic backups, and `--dry-run` mode\n- `\u002Ftokenwise:report` — per-session token + cost summary vs all-Opus baseline\n- `\u002Ftokenwise:summary [--week|--month|--all]` — historical aggregate with trend\n- `\u002Ftokenwise:ab \"\u003Ctask>\"` — A\u002FB test the same task at multiple tiers, generates a markdown comparison\n- `\u002Ftokenwise:undo` — restore CLAUDE.md \u002F settings.json from backup\n\n## Routing taxonomy\n\n| Tier | Model | Task class |\n|---|---|---|\n| Mechanical | Haiku 4.5 | file reads, grep, format, rename, simple edits, doc lookups |\n| Scoped reasoning | Sonnet 4.6 | single-file refactor, scoped research, test writing |\n| Synthesis | Opus 4.7 | architecture decisions, multi-file refactor, security review |\n\nSafety caps:\n- Haiku never spawns further subagents\n- Max spawn depth = 2\n- Subagents that need a smarter model return to parent — they never escalate on their own\n- Tasks under 100 chars with no file context run inline (subagent overhead > savings)\n- Subagent context >30k tokens bumps a tier\n\n## Privacy\n\nZero telemetry. All logs in `.tokenwise\u002Flog.ndjson` local to the project. Task descriptions truncated to 80 chars and stripped of file contents before logging. No analytics endpoint exists in the source.\n\n## Install\n\nIn any Claude Code session:\n\n```\n\u002Fplugin marketplace add CodeShuX\u002Ftokenwise\n\u002Fplugin install tokenwise@tokenwise\n```\n\nThen run `\u002Ftokenwise:install` and follow the guided prompts.\n\n## Limitations\n\n- Token counts approximate to ±2% vs Anthropic billing\n- A\u002FB test mode costs extra tokens (one task × N tiers) — intentional one-time validation\n- Anthropic-only by design (use LiteLLM or OpenRouter for cross-vendor)\n- Subagent `model:` param has known silent-fail bugs on some Claude Code builds — skill probes for this at install and refuses to configure if routing is broken\n\n## Source\n\n- Repo: https:\u002F\u002Fgithub.com\u002FCodeShuX\u002Ftokenwise\n- License: MIT\n- Author: CodeShuX\n","# TokenWise — Measurement-Driven Model Router\n\n## Overview\n\nA Claude Code skill that auto-routes subtasks to the cheapest model that can handle them (Haiku for grunt work, Sonnet for scoped reasoning, Opus only for synthesis), then logs every routed task to a local NDJSON with real token + cost numbers. Includes an A\u002FB test subcommand that runs the same task across multiple tiers and scores quality, so the routing decisions are verified against the user's real workload — not estimated.\n\nAnthropic's own bug tracker (Issue #27665) reports 93.8% of Max-subscriber Claude Code tokens flow to Opus. Existing routers (claude-router, wshobson, VoltAgent) either pin models statically or route by vibes-based heuristics with no measurement. TokenWise fills the measurement gap.\n\n## When to use\n\n- Cutting Claude Code token spend without sacrificing output quality\n- Validating whether Haiku\u002FSonnet is \"good enough\" for a specific task class before trusting auto-routing\n- Auditing where Opus tokens are actually being burned\n- Logging per-session cost data for finance or chargeback\n\n## Subcommands\n\n- `\u002Ftokenwise:install` — guided installer with diff preview, automatic backups, and `--dry-run` mode\n- `\u002Ftokenwise:report` — per-session token + cost summary vs all-Opus baseline\n- `\u002Ftokenwise:summary [--week|--month|--all]` — historical aggregate with trend\n- `\u002Ftokenwise:ab \"\u003Ctask>\"` — A\u002FB test the same task at multiple tiers, generates a markdown comparison\n- `\u002Ftokenwise:undo` — restore CLAUDE.md \u002F settings.json from backup\n\n## Routing taxonomy\n\n| Tier | Model | Task class |\n|---|---|---|\n| Mechanical | Haiku 4.5 | file reads, grep, format, rename, simple edits, doc lookups |\n| Scoped reasoning | Sonnet 4.6 | single-file refactor, scoped research, test writing |\n| Synthesis | Opus 4.7 | architecture decisions, multi-file refactor, security review |\n\nSafety caps:\n- Haiku never spawns further subagents\n- Max spawn depth = 2\n- Subagents that need a smarter model return to parent — they never escalate on their own\n- Tasks under 100 chars with no file context run inline (subagent overhead > savings)\n- Subagent context >30k tokens bumps a tier\n\n## Privacy\n\nZero telemetry. All logs in `.tokenwise\u002Flog.ndjson` local to the project. Task descriptions truncated to 80 chars and stripped of file contents before logging. No analytics endpoint exists in the source.\n\n## Install\n\nIn any Claude Code session:\n\n```\n\u002Fplugin marketplace add CodeShuX\u002Ftokenwise\n\u002Fplugin install tokenwise@tokenwise\n```\n\nThen run `\u002Ftokenwise:install` and follow the guided prompts.\n\n## Limitations\n\n- Token counts approximate to ±2% vs Anthropic billing\n- A\u002FB test mode costs extra tokens (one task × N tiers) — intentional one-time validation\n- Anthropic-only by design (use LiteLLM or OpenRouter for cross-vendor)\n- Subagent `model:` param has known silent-fail bugs on some Claude Code builds — skill probes for this at install and refuses to configure if routing is broken\n\n## Source\n\n- Repo: https:\u002F\u002Fgithub.com\u002FCodeShuX\u002Ftokenwise\n- License: MIT\n- Author: CodeShuX\n",{"name":5,"risk":30,"tags":48,"tools":57,"author":59,"plugin":60,"source":41,"license":15,"category":39,"date_added":63,"description":7,"source_repo":64,"source_type":41,"license_source":65},[49,32,50,51,52,53,54,55,56,42],"model-routing","cost-reduction","anthropic","haiku","sonnet","opus","claude-code","ab-testing",[58],"claude","CodeShuX",{"targets":61},{"codex":62,"claude":62},"blocked","2026-05-12","CodeShuX\u002Ftokenwise","https:\u002F\u002Fgithub.com\u002FCodeShuX\u002Ftokenwise\u002Fblob\u002Fmain\u002FLICENSE","681496e0662f4c45c4758fae9d4510ae87311bf2","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills","https:\u002F\u002Fgithub.com\u002Fagency-black","http:\u002F\u002Fwww.dogma.black","Las grandes ideas merecen una ejecución impecable. Construimos plataformas web, aplicaciones y ecosistemas digitales completos. Esta Trinidad es nuestro dogma.","2026-05-29 16:13:55",{"source":8,"skillName":5,"commands":73,"prompt":83,"zipAvailable":84},[74,77,80],{"tool":75,"command":76},"npx","npx skills add agency-black\u002FSkills --skill tokenwise",{"tool":78,"command":79},"bunx","bunx skills add agency-black\u002FSkills --skill tokenwise",{"tool":81,"command":82},"pnpm","pnpm dlx skills add agency-black\u002FSkills --skill tokenwise","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Ftokenwise\u002FSKILL.md",true,[],[87,113,142,170,195,220],{"skillNo":88,"name":89,"nameZh":6,"description":90,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":91,"categories":92,"keywords":93,"publishedAt":43},"01M71JZVZ0TVW7Z5DQBRWSBG8A","zarr-python","Chunked N-D arrays for cloud storage (Zarr-Python 3). Compressed arrays, parallel I\u002FO, S3\u002FGCS via fsspec, NumPy\u002FDask\u002FXarray compatible, for large-scale scientific computing pipelines.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fzarr-python\u002FSKILL.md",[],[94,95,96,97,98,99,100,101,102,103,104,105,106,36,107,108,109,110,111,112],"zarr python","python","zarr","arrays","Cloud Storage","remote","workflows","scientific","read","write","edit","parallel","dask","s3fs","use","numpy","s3","scientific computing","scale",{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":117,"sourceHtmlUrl":118,"categories":119,"keywords":125,"publishedAt":43},"01M71JYXC5VAEJT8KXN5GRK32S","xvary-stock-research","Thesis-driven equity analysis from public SEC EDGAR and market data; \u002Fanalyze, \u002Fscore, \u002Fcompare workflows with bundled Python tools (Claude Code, Cursor, Codex).","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fxvary-stock-research\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fxvary-stock-research\u002FSKILL.md",[120],{"categoryNo":121,"categoryName":122,"taxonomyType":123,"taxonomyTypeDesc":124},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[126,127,128,129,130,41,131,95,132,100,133,28,134,135,136,137,138,139,140,141],"xvary","stock","research","xvary stock research","sec edgar","equity","thesis","analysis","Market","compare","market data","analyze","with","codex","cursor","2026",{"skillNo":143,"name":144,"nameZh":6,"description":145,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":146,"licenseFileUrl":147,"sourceHtmlUrl":148,"categories":149,"keywords":156,"publishedAt":43},"01M71JVSDPDQ5040YBN6J1ASKY","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fwebapp-testing\u002FSKILL.md",[150,153],{"categoryNo":151,"categoryName":152,"taxonomyType":123,"taxonomyTypeDesc":124},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":154,"categoryName":155,"taxonomyType":123,"taxonomyTypeDesc":124},"01JBSEEDCAT000000000000009","前端开发",[157,34,158,36,159,160,161,162,163,27,164,138,165,166,167,168,169],"webapp","webapp testing","applications","local","frontend","debugging","toolkit","browser","playwright","web","behavior","ui","screenshots",{"skillNo":171,"name":172,"nameZh":6,"description":173,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":146,"licenseFileUrl":174,"sourceHtmlUrl":175,"categories":176,"keywords":178,"publishedAt":43},"01M71JV64CW7R6FYYK9JWWGW0X","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fweb-artifacts-builder\u002FSKILL.md",[177],{"categoryNo":154,"categoryName":155,"taxonomyType":123,"taxonomyTypeDesc":124},[179,180,181,166,182,183,184,36,185,186,161,187,108,188,189,190,191,192,193,194],"builder","artifacts builder","artifacts","web artifacts builder","single-file","css","Tailwind","ui components","single","file","components","react","multi","state","routing","state management",{"skillNo":196,"name":197,"nameZh":6,"description":198,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":199,"categories":200,"keywords":202,"publishedAt":43},"01M71JS4X2FRY41DE84DEP06MN","vercel-react-view-transitions","Guide for implementing smooth, native-feeling animations using React's View Transition API (`\u003CViewTransition>` component, `addTransitionType`, and CSS view transition pseudo-elements). Use this skill whenever the user wants to add page transitions, animate route changes, create shared element animations, animate enter\u002Fexit of components, animate list reorder, implement directional (forward\u002Fback) navigation animations, or integrate view transitions in Next.js. Also use when the user mentions view transitions, `startViewTransition`, `ViewTransition`, transition types, or asks about animating between UI states in React without third-party animation libraries.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fvercel-react-view-transitions\u002FSKILL.md",[201],{"categoryNo":154,"categoryName":155,"taxonomyType":123,"taxonomyTypeDesc":124},[190,203,204,205,206,207,208,209,210,184,211,212,213,214,215,189,216,217,218,219],"vercel react view transitions","view","react view transitions","vercel","transitions","shared","back","Animation","types","states","element","implementing","when","api","route","create","libraries",{"skillNo":221,"name":222,"nameZh":6,"description":223,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":224,"categories":225,"keywords":227,"publishedAt":43},"01M71JS1WZ1J4F9YVC2203JBJW","vercel-react-native-skills","React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fvercel-react-native-skills\u002FSKILL.md",[226],{"categoryNo":154,"categoryName":155,"taxonomyType":123,"taxonomyTypeDesc":124},[206,228,190,229,230,231,232,233,234,36,235,214,236,108,237,238,215,239,240,189],"vercel react native skills","react native","native","react native skills","modules","platform","animations","performance","triggers","react native components","apps","best practices","tasks"]