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Agent Skill · 研究检索

model-selection(选型)

model-selection 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

model-selection 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 55,410。

总安装 480周安装 20GitHub Stars 315下载 160核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:model-selection(选型)
来源仓库:https://github.com/codewithmukesh/dotnet-claude-kit
仓库路径:skills/model-selection
安装命令:
npx skills add https://github.com/codewithmukesh/dotnet-claude-kit --skill model-selection
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/codewithmukesh/dotnet-claude-kit --skill model-selection

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词快速定位候选结果。通过 npx skills add 命令从指定仓库安装,需确认权限和维护状态。涉及联网、命令执行或文件读写时,应先评估安全风险和操作边界。建议结合原始 README 核验具体用法和功能细节。

来源仓库内路径:skills/model-selection

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/codewithmukesh/dotnet-claude-kit --skill model…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

model-selection 怎么安装?

在终端执行 npx skills add https://github.com/codewithmukesh/dotnet-claude-kit --skill model-selection。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

model-selection 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

model-selection 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

model-selection 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

model-selection 用的人多吗?

公开数据是累计安装 480 次,近一周安装 20 次,下载 160 次,GitHub 315 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

model-selection 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
model-selection

选型 · 本页

480315需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Model Selection

Core Principles

  1. Match model to complexity, not size — A 50-file refactor that follows a clear pattern is a Sonnet task (high throughput, simple logic). A 3-file architecture decision with trade-offs is an Opus task (deep reasoning). File count and complexity are orthogonal.
  2. Sonnet is the workhorse — 80% of.NET development tasks are routine: implement a feature following an established pattern, write tests, fix a known bug, run scaffolding. Sonnet 4.6 handles all of these at higher speed and lower cost.
  3. Opus is the architect — Use Opus 4.6 for tasks that require weighing trade-offs, reasoning about system design, debugging subtle issues, or making decisions with incomplete information. Opus excels when the answer isn't obvious.
  4. Context window is a budget, not a dumping ground — Sonnet 4.6's large context window enables working with big codebases but doesn't mean you should load everything. Apply context-discipline principles regardless of model. A focused Sonnet session outperforms a bloated one.
  5. Haiku for fire-and-forget subagents — When a subagent does a simple lookup, runs a script, or fetches information, Haiku 4.5 is fast and cheap. Reserve heavier models for subagents that need to reason.

Patterns

Task Complexity Assessment

Classify each task to select the right model:

ROUTINE TASKS → Sonnet 4.6
- Implement a feature following an existing pattern
- Write tests for existing code
- Fix a bug with a clear stack trace
- Add a new endpoint matching the project's convention
- Run scaffolding or code generation
- Apply a known refactoring pattern
- Format, lint, or fix build errors
- Write documentation from existing code

COMPLEX TASKS → Opus 4.6
- Design a new module or subsystem from scratch
- Choose between architecture approaches (VSA vs CA vs DDD)
- Debug a subtle issue with no clear stack trace
- Refactor with trade-offs (performance vs readability, consistency vs simplicity)
- Review architecture for design flaws
- Make decisions with incomplete or conflicting requirements
- Untangle complex dependencies or circular references
- Write a migration strategy for breaking changes

SIMPLE TASKS → Haiku 4.5 (subagents only)
- Look up a file path or symbol location
- Run a build/test and report results
- Search for a pattern across files
- Summarize a file or module
- Format or validate data

Model Switching Workflow

The most effective pattern: Opus plans, Sonnet executes, Opus reviews.

PHASE 1: PLAN (Opus 4.6)
├── Analyze requirements and constraints
├── Identify architectural trade-offs
├── Design the approach with rationale
├── Define acceptance criteria
└── Output: detailed implementation plan

PHASE 2: EXECUTE (Sonnet 4.6)
├── Implement following the Opus plan
├── Write code, tests, configurations
├── Run build and test verification
├── Handle routine issues (compilation errors, test fixes)
└── Output: working implementation

PHASE 3: REVIEW (Opus 4.6)
├── Review implementation against the plan
├── Check for subtle issues (race conditions, N+1, security)
├── Evaluate architectural compliance
├── Suggest refinements
└── Output: approval or specific revision requests

How to switch in practice:

Claude Code CLI:
- /model opus    → Switch to Opus 4.6 (planning/review phases)
- /model sonnet  → Switch to Sonnet 4.6 (implementation phase)
- /model auto    → Let Claude Code choose based on task

Toggle fast mode:
- /fast          → Toggle fast mode (Opus fast output for throughput)

Subagent Model Assignment

Assign models to subagents based on task complexity:

SUBAGENT: "Find all authentication middleware in the project"
→ MODEL: Haiku 4.5
→ WHY: Simple search task, no reasoning required

SUBAGENT: "Run dotnet test and summarize failures"
→ MODEL: Haiku 4.5
→ WHY: Execute command, parse output, no complex analysis

SUBAGENT: "Analyze the dependency graph for circular references and suggest fixes"
→ MODEL: Sonnet 4.6
→ WHY: Needs to understand project structure and propose solutions

SUBAGENT: "Review this PR for architectural issues and security vulnerabilities"
→ MODEL: Opus 4.6
→ WHY: Deep reasoning about trade-offs, subtle issue detection

SUBAGENT: "Summarize what the Orders module does"
→ MODEL: Haiku 4.5 or Sonnet 4.6
→ WHY: Haiku for a quick overview, Sonnet if the module is complex

Anti-patterns

Using Opus for Simple Tasks

// BAD — Opus for a routine CRUD endpoint
Using Opus 4.6 to implement GetOrderById following the exact same pattern
as the existing GetCustomerById. No decisions to make, just pattern replication.
*Slower and more expensive than needed*

// GOOD — Sonnet for pattern replication
Using Sonnet 4.6 to implement GetOrderById. The pattern is established,
the code is straightforward, and Sonnet executes it faster.

Using Sonnet for Architecture Decisions

// BAD — Sonnet for "should we use VSA or Clean Architecture?"
Sonnet gives a reasonable answer but may miss nuanced trade-offs
about team size, domain complexity, and long-term maintenance.
*The wrong architecture costs months of refactoring*

// GOOD — Opus for architectural decisions
Opus weighs team size, domain complexity, current codebase patterns,
and long-term implications. The architecture decision is worth the
extra reasoning power.

Same Model for All Subagents

// BAD — all subagents use Opus
5 subagents running Opus 4.6:
- "Find OrderService.cs" (Haiku could do this)
- "Run dotnet test" (Haiku could do this)
- "Summarize the Catalog module" (Haiku/Sonnet could do this)
- "Analyze circular dependencies" (Sonnet is sufficient)
- "Review architecture for security issues" (Opus is appropriate)
*4 out of 5 subagents are using more model than needed*

// GOOD — model matches subagent task
- "Find OrderService.cs" → Haiku 4.5
- "Run dotnet test" → Haiku 4.5
- "Summarize the Catalog module" → Haiku 4.5
- "Analyze circular dependencies" → Sonnet 4.6
- "Review architecture for security issues" → Opus 4.6

Decision Guide

ScenarioModelRationale
Plan a new feature or moduleOpus 4.6Requires weighing trade-offs
Implement a feature following existing patternsSonnet 4.6Pattern replication, high throughput
Debug a subtle intermittent issueOpus 4.6Requires deep reasoning about state/timing
Fix a compilation errorSonnet 4.6Clear error, mechanical fix
Write tests for existing codeSonnet 4.6Test patterns are established
Architecture review / PR reviewOpus 4.6Subtle issues need deep analysis
Code review for anti-patternsSonnet 4.6Pattern matching, well-defined rules
Refactor across many files (same pattern)Sonnet 4.6Volume + consistency, not deep reasoning
Design database schema from requirementsOpus 4.6Normalization trade-offs, domain modeling
Subagent: file lookup or searchHaiku 4.5Simple task, fast and cheap
Subagent: summarize a moduleHaiku 4.5Straightforward reading + compression
Subagent: analyze dependenciesSonnet 4.6Needs to reason about structure
Working in a very large codebaseSonnet 4.6Large context window + discipline
End-of-day wrap-up / handoffSonnet 4.6Structured capture, no deep reasoning

平台分布

Codex

32.55%
按下载量换算52

Claude

32.07%
按下载量换算51

Cursor

19.5%
按下载量换算31

Gemini CLI

9.61%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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