Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add kevintsengtw/dotnet-testing-agent-skills --skill dotnet-testing-autodata-xunit-integrationgit clone --depth 1 https://github.com/kevintsengtw/dotnet-testing-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/kevintsengtw/dotnet-testing-agent-skills/dotnet-testing-autodata-xunit-integration)<a href="https://agentmods.dev/skills/kevintsengtw/dotnet-testing-agent-skills/dotnet-testing-autodata-xunit-integration"><img src="https://agentmods.dev/badge/skills/kevintsengtw/dotnet-testing-agent-skills/dotnet-testing-autodata-xunit-integration/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/kevintsengtw/dotnet-testing-agent-skills/dotnet-testing-autodata-xunit-integration"><img src="https://agentmods.dev/badge/skills/kevintsengtw/dotnet-testing-agent-skills/dotnet-testing-autodata-xunit-integration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00181 | $0.03997 |
| Opus 5 | $0.00090 | $0.01998 |
| Sonnet 5 | $0.00036 | $0.00799 |
| Haiku 4.5 | $0.00018 | $0.00400 |
Grade A, and why
dotnet-testing-autodata-xunit-integration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 459 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AutoData 屬性家族:xUnit 與 AutoFixture 的整合應用
概述
AutoData 屬性家族是 AutoFixture.Xunit2 套件提供的功能,將 AutoFixture 的資料產生能力與 xUnit 的參數化測試整合,讓測試參數自動注入,大幅減少測試準備程式碼。
核心特色
- AutoData:自動產生所有測試參數
- InlineAutoData:混合固定值與自動產生
- MemberAutoData:結合外部資料來源
- CompositeAutoData:多重資料來源整合
- CollectionSizeAttribute:控制集合產生數量
安裝套件
<PackageReference Include="AutoFixture" Version="4.18.1" />
<PackageReference Include="AutoFixture.Xunit2" Version="4.18.1" />
dotnet add package AutoFixture.Xunit2
AutoData:完全自動產生參數
AutoData 是最基礎的屬性,自動為測試方法的所有參數產生測試資料。
基本使用
using AutoFixture.Xunit2;
public class Person
{
public Guid Id { get; set; }
[StringLength(10)]
public string Name { get; set; } = string.Empty;
[Range(18, 80)]
public int Age { get; set; }
public string Email { get; set; } = string.Empty;
public DateTime CreateTime { get; set; }
}
[Theory]
[AutoData]
public void AutoData_應能自動產生所有參數(Person person, string message, int count)
{
// Arrange & Act - 參數已由 AutoData 自動產生
// Assert
person.Should().NotBeNull();
person.Id.Should().NotBe(Guid.Empty);
person.Name.Should().HaveLength(10); // 遵循 StringLength 限制
person.Age.Should().BeInRange(18, 80); // 遵循 Range 限制
message.Should().NotBeNullOrEmpty();
count.Should().NotBe(0);
}
透過 DataAnnotation 約束參數
[Theory]
[AutoData]
public void AutoData_透過DataAnnotation約束參數(
[StringLength(5, MinimumLength = 3)] string shortName,
[Range(1, 100)] int percentage,
Person person)
{
// Assert
shortName.Length.Should().BeInRange(3, 5);
percentage.Should().BeInRange(1, 100);
person.Should().NotBeNull();
}
InlineAutoData:混合固定值與自動產生
InlineAutoData 結合了 InlineData 的固定值特性與 AutoData 的自動產生功能。
基本語法
[Theory]
[InlineAutoData("VIP客戶", 1000)]
[InlineAutoData("一般客戶", 500)]
[InlineAutoData("新客戶", 100)]
public void InlineAutoData_混合固定值與自動產生(
string customerType, // 對應第 1 個固定值
decimal creditLimit, // 對應第 2 個固定值
Person person) // 由 AutoFixture 產生
{
// Arrange
var customer = new Customer
{
Person = person,
Type = customerType,
CreditLimit = creditLimit
};
// Assert
customer.Type.Should().Be(customerType);
customer.CreditLimit.Should().BeOneOf(1000, 500, 100);
customer.Person.Should().NotBeNull();
}
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 459 lines · 181 tokens per session scan A 8138d8670864
dotnet-testing-autodata-xunit-integration is a skill published in the GitHub repository kevintsengtw/dotnet-testing-agent-skills (28 stars, last pushed 25d ago), licensed MIT. It adds 181 tokens to every session and 3,997 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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