[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71MQJXRM1SAKHPVAHZ95EQY":3,"skill-same:01M71MQJXRM1SAKHPVAHZ95EQY":291},{"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":28,"publishedAt":48,"linkOnly":49,"markdownContent":50,"markdownBody":51,"frontMatter":52,"refName":60,"commitSha":61,"skillDirectory":62,"forksCount":14,"repositoryHtmlUrl":63,"repositoryHomepageUrl":64,"ownerHtmlUrl":65,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":66,"install":67,"resources":80},"01M71MQJXRM1SAKHPVAHZ95EQY","cuopt-numerical-optimization-api",null,"LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface.","pattanation\u002FNorvik","pattanation","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F235419268?v=4","01M71M5THHYYB15ME8R2E4FCZG","Patta","01M71M5TJM1NDM992M8PDKYR2K",0,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47],"numerical","api","cuopt numerical optimization api","Optimization","linear","user","cli","with","programming","team","lp","when","use","interface","beta","python","NVIDIA","qp","linear-programming","2026-11-10 10:56:23",false,"---\nname: cuopt-numerical-optimization-api\nversion: \"26.08.00\"\ndescription: LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface.\nlicense: Apache-2.0\nmetadata:\n  author: NVIDIA cuOpt Team\n  tags:\n    - cuopt\n    - linear-programming\n    - milp\n    - qp\n    - python\n    - c-api\n    - cli\n---\n\n\n# cuOpt Numerical Optimization API\n\nModel and solve LP, MILP, and QP problems using NVIDIA cuOpt's GPU-accelerated solver.\n\n## Interface Selection\n\nChoose the reference for the user's interface:\n\n| Interface | When to use | Reference |\n|-----------|-------------|-----------|\n| **Python** | User is writing Python code | [references\u002Fpython_api.md](references\u002Fpython_api.md) |\n| **C \u002F C++** | User is embedding in a C\u002FC++ application | [references\u002Fc_api.md](references\u002Fc_api.md) |\n| **CLI** | User is solving from MPS files on the command line | [references\u002Fcli_api.md](references\u002Fcli_api.md) |\n\nIf the interface is not yet clear, ask before writing any code.\n\n**Already using a modeling language?** cuOpt also works as a solver backend for third-party\nmodeling tools — **AMPL, GAMS \u002F GAMSPy, PuLP, JuMP, Pyomo, and CVXPY** — with near-zero code\nchanges (point the model's solver at cuOpt). CVXPY additionally covers convex QP and, in beta,\nQCQP \u002F SOCP. Prefer this when the user already has a model in one of these tools rather than porting\nit to the cuOpt API. See\n[Third-Party Modeling Languages](https:\u002F\u002Fdocs.nvidia.com\u002Fcuopt\u002Fuser-guide\u002Flatest\u002Fthirdparty_modeling_languages\u002Findex.html).\n\n## Choosing LP vs MILP vs QP\n\n**Decide from the objective and variables:**\n\n| If the objective is... | And variables are... | Use |\n|---|---|---|\n| Linear (sum of `c_i * x_i`) | All continuous | **LP** |\n| Linear | Some integer or binary | **MILP** |\n| Has squared (`x*x`) or cross (`x*y`) terms | Continuous (integer QP not supported) | **QP** (beta) |\n\n**Prefer LP when the problem allows it.** LP solves faster and has stronger optimality guarantees. Use MILP only when the problem logically requires whole numbers or yes\u002Fno decisions. Use QP only when the objective is genuinely quadratic (variance, squared error, kinetic energy).\n\n- **Use LP** when every quantity can meaningfully be fractional: flows, proportions, rates, dollars, hours, tonnes of material, etc.\n- **Use MILP** when the problem mentions **counts** of discrete entities, **yes\u002Fno** choices, or **either\u002For** decisions (e.g. open a facility or not, assign a person to a shift, number of trucks).\n- **Use QP** when the objective minimizes variance, squared error, or any expression with `x*x` or `x*y` terms (portfolio optimization, least squares, regularized regression).\n\n## Integer vs Continuous from Wording\n\n| Problem wording \u002F concept | Variable type | Examples |\n|---------------------------|---------------|----------|\n| **Discrete entities (counts)** | **INTEGER** | Workers, cars, trucks, machines, pilots, facilities, units to manufacture |\n| **Yes\u002Fno or on\u002Foff** | **INTEGER** (binary, lb=0 ub=1) | Open a facility, run a machine, assign a person to a shift |\n| **Amounts that can be fractional** | **CONTINUOUS** | Tonnes, litres, dollars, hours, kWh, proportion of capacity |\n| **Rates or fractions** | **CONTINUOUS** | Utilization, percentage, share of budget |\n\n**Rule of thumb:** \"How many *things*\" → INTEGER. \"How much\" → CONTINUOUS.\n\n## QP Rules (all interfaces)\n\n- **MINIMIZE only** — the solver rejects MAXIMIZE for quadratic objectives. To maximize `f(x)`, minimize `-f(x)` and negate the reported objective value.\n- **Continuous variables only** — integer QP is not supported.\n- **Q should be positive semi-definite** for a convex, well-posed problem.\n- **Beta** — API may evolve; treat as production-capable for typical convex QP.\n\n## Dual Values\n\nDuals and reduced costs are available for **LP and QP only**:\n- **MILP** — no duals (integer optima are not continuous).\n- **Quadratic constraints** — duals unavailable even for LP\u002FQP; all values return `NaN`.\n- **PDLP warmstart** — LP only; MILP solves do not accept a PDLP warmstart.\n\n## Common Issues (all interfaces)\n\n| Problem | Likely cause | Fix |\n|---------|-------------|-----|\n| Infeasible | Conflicting constraints | Check constraint logic and bounds |\n| Unbounded | Missing bounds | Add variable bounds |\n| Slow solve | Large problem | Set time limit; increase gap tolerance |\n| QP rejected with MAXIMIZE | QP only supports MINIMIZE | Negate the objective; negate the result |\n| QP returns non-optimal | Q not PSD or badly scaled | Check Q is PSD; rescale variables |\n\n## Solver Settings (concepts)\n\n| Setting | Purpose |\n|---------|---------|\n| `time_limit` | Stop after N seconds |\n| `mip_relative_gap` | Stop MILP when within X% of optimal |\n| `mip_absolute_tolerance` | Absolute MIP gap stop |\n| `log_to_console` | Enable solver logging |\n\nSyntax varies by interface — see the interface reference file.\n","# cuOpt Numerical Optimization API\n\nModel and solve LP, MILP, and QP problems using NVIDIA cuOpt's GPU-accelerated solver.\n\n## Interface Selection\n\nChoose the reference for the user's interface:\n\n| Interface | When to use | Reference |\n|-----------|-------------|-----------|\n| **Python** | User is writing Python code | [references\u002Fpython_api.md](references\u002Fpython_api.md) |\n| **C \u002F C++** | User is embedding in a C\u002FC++ application | [references\u002Fc_api.md](references\u002Fc_api.md) |\n| **CLI** | User is solving from MPS files on the command line | [references\u002Fcli_api.md](references\u002Fcli_api.md) |\n\nIf the interface is not yet clear, ask before writing any code.\n\n**Already using a modeling language?** cuOpt also works as a solver backend for third-party\nmodeling tools — **AMPL, GAMS \u002F GAMSPy, PuLP, JuMP, Pyomo, and CVXPY** — with near-zero code\nchanges (point the model's solver at cuOpt). CVXPY additionally covers convex QP and, in beta,\nQCQP \u002F SOCP. Prefer this when the user already has a model in one of these tools rather than porting\nit to the cuOpt API. See\n[Third-Party Modeling Languages](https:\u002F\u002Fdocs.nvidia.com\u002Fcuopt\u002Fuser-guide\u002Flatest\u002Fthirdparty_modeling_languages\u002Findex.html).\n\n## Choosing LP vs MILP vs QP\n\n**Decide from the objective and variables:**\n\n| If the objective is... | And variables are... | Use |\n|---|---|---|\n| Linear (sum of `c_i * x_i`) | All continuous | **LP** |\n| Linear | Some integer or binary | **MILP** |\n| Has squared (`x*x`) or cross (`x*y`) terms | Continuous (integer QP not supported) | **QP** (beta) |\n\n**Prefer LP when the problem allows it.** LP solves faster and has stronger optimality guarantees. Use MILP only when the problem logically requires whole numbers or yes\u002Fno decisions. Use QP only when the objective is genuinely quadratic (variance, squared error, kinetic energy).\n\n- **Use LP** when every quantity can meaningfully be fractional: flows, proportions, rates, dollars, hours, tonnes of material, etc.\n- **Use MILP** when the problem mentions **counts** of discrete entities, **yes\u002Fno** choices, or **either\u002For** decisions (e.g. open a facility or not, assign a person to a shift, number of trucks).\n- **Use QP** when the objective minimizes variance, squared error, or any expression with `x*x` or `x*y` terms (portfolio optimization, least squares, regularized regression).\n\n## Integer vs Continuous from Wording\n\n| Problem wording \u002F concept | Variable type | Examples |\n|---------------------------|---------------|----------|\n| **Discrete entities (counts)** | **INTEGER** | Workers, cars, trucks, machines, pilots, facilities, units to manufacture |\n| **Yes\u002Fno or on\u002Foff** | **INTEGER** (binary, lb=0 ub=1) | Open a facility, run a machine, assign a person to a shift |\n| **Amounts that can be fractional** | **CONTINUOUS** | Tonnes, litres, dollars, hours, kWh, proportion of capacity |\n| **Rates or fractions** | **CONTINUOUS** | Utilization, percentage, share of budget |\n\n**Rule of thumb:** \"How many *things*\" → INTEGER. \"How much\" → CONTINUOUS.\n\n## QP Rules (all interfaces)\n\n- **MINIMIZE only** — the solver rejects MAXIMIZE for quadratic objectives. To maximize `f(x)`, minimize `-f(x)` and negate the reported objective value.\n- **Continuous variables only** — integer QP is not supported.\n- **Q should be positive semi-definite** for a convex, well-posed problem.\n- **Beta** — API may evolve; treat as production-capable for typical convex QP.\n\n## Dual Values\n\nDuals and reduced costs are available for **LP and QP only**:\n- **MILP** — no duals (integer optima are not continuous).\n- **Quadratic constraints** — duals unavailable even for LP\u002FQP; all values return `NaN`.\n- **PDLP warmstart** — LP only; MILP solves do not accept a PDLP warmstart.\n\n## Common Issues (all interfaces)\n\n| Problem | Likely cause | Fix |\n|---------|-------------|-----|\n| Infeasible | Conflicting constraints | Check constraint logic and bounds |\n| Unbounded | Missing bounds | Add variable bounds |\n| Slow solve | Large problem | Set time limit; increase gap tolerance |\n| QP rejected with MAXIMIZE | QP only supports MINIMIZE | Negate the objective; negate the result |\n| QP returns non-optimal | Q not PSD or badly scaled | Check Q is PSD; rescale variables |\n\n## Solver Settings (concepts)\n\n| Setting | Purpose |\n|---------|---------|\n| `time_limit` | Stop after N seconds |\n| `mip_relative_gap` | Stop MILP when within X% of optimal |\n| `mip_absolute_tolerance` | Absolute MIP gap stop |\n| `log_to_console` | Enable solver logging |\n\nSyntax varies by interface — see the interface reference file.\n",{"name":5,"license":15,"version":53,"metadata":54,"description":7},"26.08.00",{"tags":55,"author":59},[56,47,57,46,44,58,35],"cuopt","milp","c-api","NVIDIA cuOpt Team","claude\u002Finstall-gsd-build-foQdV","d86cd127f527124b5fd0fd0bc679a4d79b7d01d7",".agents\u002Fskills\u002Fcuopt-numerical-optimization-api","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik","https:\u002F\u002Fnorvik-orpin.vercel.app","https:\u002F\u002Fgithub.com\u002Fpattanation","2026-07-17 11:17:04",{"source":8,"skillName":5,"commands":68,"prompt":78,"zipAvailable":79},[69,72,75],{"tool":70,"command":71},"npx","npx skills add pattanation\u002FNorvik --skill cuopt-numerical-optimization-api",{"tool":73,"command":74},"bunx","bunx skills add pattanation\u002FNorvik --skill cuopt-numerical-optimization-api",{"tool":76,"command":77},"pnpm","pnpm dlx skills add pattanation\u002FNorvik --skill cuopt-numerical-optimization-api","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002FSKILL.md",true,[81,87,91,95,99,103,107,111,115,119,123,127,131,135,139,143,147,150,154,158,162,168,172,176,180,184,188,192,196,200,204,208,212,216,220,224,228,231,235,239,243,247,251,255,261,265,269,273,277,281,285],{"path":82,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":85,"sourceHtmlUrl":86},"assets\u002Fc\u002Flp_basic\u002Flp_simple.c","ASSET","资产文件",3705,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002Flp_basic\u002Flp_simple.c",{"path":88,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":89,"sourceHtmlUrl":90},"assets\u002Fc\u002Flp_basic\u002FREADME.md",466,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002Flp_basic\u002FREADME.md",{"path":92,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":93,"sourceHtmlUrl":94},"assets\u002Fc\u002Flp_duals\u002Flp_duals.c",4060,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002Flp_duals\u002Flp_duals.c",{"path":96,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":97,"sourceHtmlUrl":98},"assets\u002Fc\u002Flp_duals\u002FREADME.md",500,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002Flp_duals\u002FREADME.md",{"path":100,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":101,"sourceHtmlUrl":102},"assets\u002Fc\u002Flp_warmstart\u002FREADME.md",289,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002Flp_warmstart\u002FREADME.md",{"path":104,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":105,"sourceHtmlUrl":106},"assets\u002Fc\u002Fmilp_basic\u002Fmilp_simple.c",3463,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002Fmilp_basic\u002Fmilp_simple.c",{"path":108,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":109,"sourceHtmlUrl":110},"assets\u002Fc\u002Fmilp_basic\u002FREADME.md",405,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002Fmilp_basic\u002FREADME.md",{"path":112,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":113,"sourceHtmlUrl":114},"assets\u002Fc\u002Fmilp_production_planning\u002Fmilp_production.c",3546,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002Fmilp_production_planning\u002Fmilp_production.c",{"path":116,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":117,"sourceHtmlUrl":118},"assets\u002Fc\u002Fmilp_production_planning\u002FREADME.md",459,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002Fmilp_production_planning\u002FREADME.md",{"path":120,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":121,"sourceHtmlUrl":122},"assets\u002Fc\u002Fmps_solver\u002Fdata\u002Fsample.mps",490,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002Fmps_solver\u002Fdata\u002Fsample.mps",{"path":124,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":125,"sourceHtmlUrl":126},"assets\u002Fc\u002Fmps_solver\u002Fmps_solver.c",3493,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002Fmps_solver\u002Fmps_solver.c",{"path":128,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":129,"sourceHtmlUrl":130},"assets\u002Fc\u002Fmps_solver\u002FREADME.md",590,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002Fmps_solver\u002FREADME.md",{"path":132,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":133,"sourceHtmlUrl":134},"assets\u002Fc\u002FREADME.md",1712,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fc\u002FREADME.md",{"path":136,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":137,"sourceHtmlUrl":138},"assets\u002Fcli\u002Flp_production\u002Fproduction.mps",375,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fcli\u002Flp_production\u002Fproduction.mps",{"path":140,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":141,"sourceHtmlUrl":142},"assets\u002Fcli\u002Flp_production\u002FREADME.md",192,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fcli\u002Flp_production\u002FREADME.md",{"path":144,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":145,"sourceHtmlUrl":146},"assets\u002Fcli\u002Flp_simple\u002FREADME.md",191,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fcli\u002Flp_simple\u002FREADME.md",{"path":148,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":121,"sourceHtmlUrl":149},"assets\u002Fcli\u002Flp_simple\u002Fsample.mps","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fcli\u002Flp_simple\u002Fsample.mps",{"path":151,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":152,"sourceHtmlUrl":153},"assets\u002Fcli\u002Fmilp_facility\u002Ffacility.mps",694,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fcli\u002Fmilp_facility\u002Ffacility.mps",{"path":155,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":156,"sourceHtmlUrl":157},"assets\u002Fcli\u002Fmilp_facility\u002FREADME.md",199,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fcli\u002Fmilp_facility\u002FREADME.md",{"path":159,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":160,"sourceHtmlUrl":161},"assets\u002Fcli\u002FREADME.md",856,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fcli\u002FREADME.md",{"path":163,"resourceType":164,"resourceTypeDesc":165,"sizeBytes":166,"sourceHtmlUrl":167},"assets\u002Fpython\u002Fleast_squares\u002Fmodel.py","SCRIPT","脚本",831,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fleast_squares\u002Fmodel.py",{"path":169,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":170,"sourceHtmlUrl":171},"assets\u002Fpython\u002Fleast_squares\u002FREADME.md",136,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fleast_squares\u002FREADME.md",{"path":173,"resourceType":164,"resourceTypeDesc":165,"sizeBytes":174,"sourceHtmlUrl":175},"assets\u002Fpython\u002Flp_basic\u002Fmodel.py",1122,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Flp_basic\u002Fmodel.py",{"path":177,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":178,"sourceHtmlUrl":179},"assets\u002Fpython\u002Flp_basic\u002FREADME.md",207,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Flp_basic\u002FREADME.md",{"path":181,"resourceType":164,"resourceTypeDesc":165,"sizeBytes":182,"sourceHtmlUrl":183},"assets\u002Fpython\u002Flp_duals\u002Fmodel.py",1213,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Flp_duals\u002Fmodel.py",{"path":185,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":186,"sourceHtmlUrl":187},"assets\u002Fpython\u002Flp_duals\u002FREADME.md",227,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Flp_duals\u002FREADME.md",{"path":189,"resourceType":164,"resourceTypeDesc":165,"sizeBytes":190,"sourceHtmlUrl":191},"assets\u002Fpython\u002Flp_warmstart\u002Fmodel.py",1860,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Flp_warmstart\u002Fmodel.py",{"path":193,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":194,"sourceHtmlUrl":195},"assets\u002Fpython\u002Flp_warmstart\u002FREADME.md",140,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Flp_warmstart\u002FREADME.md",{"path":197,"resourceType":164,"resourceTypeDesc":165,"sizeBytes":198,"sourceHtmlUrl":199},"assets\u002Fpython\u002Fmaximization_workaround\u002Fmodel.py",736,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fmaximization_workaround\u002Fmodel.py",{"path":201,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":202,"sourceHtmlUrl":203},"assets\u002Fpython\u002Fmaximization_workaround\u002FREADME.md",152,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fmaximization_workaround\u002FREADME.md",{"path":205,"resourceType":164,"resourceTypeDesc":165,"sizeBytes":206,"sourceHtmlUrl":207},"assets\u002Fpython\u002Fmilp_basic\u002Fincumbent_callback.py",1857,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fmilp_basic\u002Fincumbent_callback.py",{"path":209,"resourceType":164,"resourceTypeDesc":165,"sizeBytes":210,"sourceHtmlUrl":211},"assets\u002Fpython\u002Fmilp_basic\u002Fmodel.py",1184,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fmilp_basic\u002Fmodel.py",{"path":213,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":214,"sourceHtmlUrl":215},"assets\u002Fpython\u002Fmilp_basic\u002FREADME.md",433,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fmilp_basic\u002FREADME.md",{"path":217,"resourceType":164,"resourceTypeDesc":165,"sizeBytes":218,"sourceHtmlUrl":219},"assets\u002Fpython\u002Fmilp_production_planning\u002Fmodel.py",1235,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fmilp_production_planning\u002Fmodel.py",{"path":221,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":222,"sourceHtmlUrl":223},"assets\u002Fpython\u002Fmilp_production_planning\u002FREADME.md",165,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fmilp_production_planning\u002FREADME.md",{"path":225,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":226,"sourceHtmlUrl":227},"assets\u002Fpython\u002Fmps_solver\u002Fdata\u002FREADME.md",2025,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fmps_solver\u002Fdata\u002FREADME.md",{"path":229,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":121,"sourceHtmlUrl":230},"assets\u002Fpython\u002Fmps_solver\u002Fdata\u002Fsample.mps","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fmps_solver\u002Fdata\u002Fsample.mps",{"path":232,"resourceType":164,"resourceTypeDesc":165,"sizeBytes":233,"sourceHtmlUrl":234},"assets\u002Fpython\u002Fmps_solver\u002Fmodel.py",8409,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fmps_solver\u002Fmodel.py",{"path":236,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":237,"sourceHtmlUrl":238},"assets\u002Fpython\u002Fmps_solver\u002FREADME.md",2248,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fmps_solver\u002FREADME.md",{"path":240,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":241,"sourceHtmlUrl":242},"assets\u002Fpython\u002Fmps_solver\u002Fresults.md",2521,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fmps_solver\u002Fresults.md",{"path":244,"resourceType":164,"resourceTypeDesc":165,"sizeBytes":245,"sourceHtmlUrl":246},"assets\u002Fpython\u002Fportfolio\u002Fmodel.py",1610,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fportfolio\u002Fmodel.py",{"path":248,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":249,"sourceHtmlUrl":250},"assets\u002Fpython\u002Fportfolio\u002FREADME.md",232,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002Fportfolio\u002FREADME.md",{"path":252,"resourceType":83,"resourceTypeDesc":84,"sizeBytes":253,"sourceHtmlUrl":254},"assets\u002Fpython\u002FREADME.md",581,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fassets\u002Fpython\u002FREADME.md",{"path":256,"resourceType":257,"resourceTypeDesc":258,"sizeBytes":259,"sourceHtmlUrl":260},"BENCHMARK.md","REFERENCE","参考文档",3886,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002FBENCHMARK.md",{"path":262,"resourceType":257,"resourceTypeDesc":258,"sizeBytes":263,"sourceHtmlUrl":264},"evals\u002Fevals.json",13978,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fevals\u002Fevals.json",{"path":266,"resourceType":257,"resourceTypeDesc":258,"sizeBytes":267,"sourceHtmlUrl":268},"references\u002Fc_api.md",4811,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Freferences\u002Fc_api.md",{"path":270,"resourceType":257,"resourceTypeDesc":258,"sizeBytes":271,"sourceHtmlUrl":272},"references\u002Fcli_api.md",5621,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Freferences\u002Fcli_api.md",{"path":274,"resourceType":257,"resourceTypeDesc":258,"sizeBytes":275,"sourceHtmlUrl":276},"references\u002Fpython_api.md",4789,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Freferences\u002Fpython_api.md",{"path":278,"resourceType":257,"resourceTypeDesc":258,"sizeBytes":279,"sourceHtmlUrl":280},"references\u002Fqp_examples.md",5800,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Freferences\u002Fqp_examples.md",{"path":282,"resourceType":257,"resourceTypeDesc":258,"sizeBytes":283,"sourceHtmlUrl":284},"skill-card.md",4225,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fskill-card.md",{"path":286,"resourceType":287,"resourceTypeDesc":288,"sizeBytes":289,"sourceHtmlUrl":290},"skill.oms.sig","OTHER","其他",16285,"https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fcuopt-numerical-optimization-api\u002Fskill.oms.sig",[292,323,348,372,394,409],{"skillNo":293,"name":294,"nameZh":6,"description":295,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":296,"sourceHtmlUrl":297,"categories":298,"keywords":305,"publishedAt":322},"01M71QDV4DM8T19HEHWATEF1K4","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.","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fwebapp-testing\u002FSKILL.md",[299,302],{"categoryNo":300,"categoryName":301,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":303,"categoryName":304,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[306,307,308,309,310,311,312,313,314,315,316,36,317,318,319,320,321],"webapp","testing","webapp testing","for","applications","local","frontend","debugging","toolkit","logs","browser","playwright","web","behavior","ui","screenshots","2026-11-10 13:02:02",{"skillNo":324,"name":325,"nameZh":6,"description":326,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":327,"sourceHtmlUrl":328,"categories":329,"keywords":331,"publishedAt":322},"01M71QDH2GGMXGA9105C9W1N7B","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\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fweb-artifacts-builder\u002FSKILL.md",[330],{"categoryNo":303,"categoryName":304,"taxonomyType":21,"taxonomyTypeDesc":22},[332,333,334,318,335,336,337,309,338,339,312,340,41,341,342,343,344,345,346,347],"builder","artifacts builder","artifacts","web artifacts builder","single-file","css","Tailwind","ui components","single","file","components","react","multi","state","routing","state management",{"skillNo":349,"name":350,"nameZh":6,"description":351,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":352,"licenseFileUrl":353,"sourceHtmlUrl":354,"categories":355,"keywords":357,"publishedAt":322},"01M71QD9T2XC3EWMQNN9ACNWQ1","vueuse-functions","Apply VueUse composables where appropriate to build concise, maintainable Vue.js \u002F Nuxt features.","MIT","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fvueuse-functions\u002FLICENSE.md","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fvueuse-functions\u002FSKILL.md",[356],{"categoryNo":303,"categoryName":304,"taxonomyType":21,"taxonomyTypeDesc":22},[358,359,360,361,362,363,364,365,366,367,368,369,370,371],"functions","vueuse","vueuse functions","project","nuxt","apply","github","concise","build","https","features","vue","js","composables",{"skillNo":373,"name":374,"nameZh":6,"description":375,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":352,"licenseFileUrl":376,"sourceHtmlUrl":377,"categories":378,"keywords":381,"publishedAt":322},"01M71QD51HWSGYMCMB7RW7PGK8","vue-testing-best-practices","Use for Vue.js testing. Covers Vitest, Vue Test Utils, component testing, mocking, testing patterns, and Playwright for E2E testing.","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fvue-testing-best-practices\u002FLICENSE.md","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fvue-testing-best-practices\u002FSKILL.md",[379,380],{"categoryNo":300,"categoryName":301,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":303,"categoryName":304,"taxonomyType":21,"taxonomyTypeDesc":22},[382,307,383,369,384,317,385,386,387,364,388,309,389,390,391,41,392,370,393],"vue testing best practices","testing best practices","best practices","test","testing patterns","component","vitest","mocking","e2e","utils","patterns","e2e testing",{"skillNo":395,"name":396,"nameZh":6,"description":397,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":352,"licenseFileUrl":398,"sourceHtmlUrl":399,"categories":400,"keywords":402,"publishedAt":322},"01M71QD358H2DJ9THJRBP77T3T","vue-router-best-practices","Vue Router 4 patterns, navigation guards, route params, and route-component lifecycle interactions.","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fvue-router-best-practices\u002FLICENSE.md","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fvue-router-best-practices\u002FSKILL.md",[401],{"categoryNo":303,"categoryName":304,"taxonomyType":21,"taxonomyTypeDesc":22},[403,369,404,384,405,387,406,364,392,407,408],"router","vue router best practices","route","guards","navigation","lifecycle",{"skillNo":410,"name":411,"nameZh":6,"description":412,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":352,"licenseFileUrl":413,"sourceHtmlUrl":414,"categories":415,"keywords":417,"publishedAt":322},"01M71QCYPNWDE2MQZ1TF3ED5S4","vue-best-practices","MUST be used for Vue.js tasks. Strongly recommends Composition API with `\u003Cscript setup>` and TypeScript as the standard approach. Covers Vue 3, SSR, Volar, vue-tsc. Load for any Vue, .vue files, Vue Router, Pinia, or Vite with Vue work. ALWAYS use Composition API unless the project explicitly requires Options API.","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fvue-best-practices\u002FLICENSE.md","https:\u002F\u002Fgithub.com\u002Fpattanation\u002FNorvik\u002Fblob\u002Fclaude\u002Finstall-gsd-build-foQdV\u002F.agents\u002Fskills\u002Fvue-best-practices\u002FSKILL.md",[416],{"categoryNo":303,"categoryName":304,"taxonomyType":21,"taxonomyTypeDesc":22},[418,369,384,419,361,420,421,30,403,422,423,424,425,426,427,309,428,41,429,430],"vue best practices","Composition","files","tasks","pinia","work","options","ssr","typescript","as","vite","load","standard"]