agentleFS
Sign inStart free
TsinHzlTsinHzl/claude-code-config/skills/swift-protocol-di-testing/SKILL.md

swift-protocol-di-testing

Skill2 starsChanged 5 months agoNo licenceView on GitHub

基于协议的依赖注入（Protocol-based Dependency Injection），通过精简的协议和 Swift 测试框架（Swift Testing）来模拟文件系统、网络和外部 API，编写可测试的 Swift 代码。

16 other projects use a version of this, 16 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use nuxt4-patterns, ralphinho-rfc-pipeline and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • loulanyueSkill

    nuxt4-patterns

    Nuxt 4 app patterns for hydration safety, performance, route rules, lazy loading, and SSR-safe data fetching with useFetch and useAsyncData.

    Also in 8 projects that use this

  • junimnjwSkill

    ralphinho-rfc-pipeline

    RFC-driven multi-agent DAG execution pattern with quality gates, merge queues, and work unit orchestration.

    Also in 9 projects that use this

  • loulanyueSkill

    santa-method

    Multi-agent adversarial verification with convergence loop. Two independent review agents must both pass before output ships.

    Also in 6 projects that use this

  • junimnjwSkill

    carrier-relationship-management

    Codified expertise for managing carrier portfolios, negotiating freight rates, tracking carrier performance, allocating freight, and maintaining strategic carrier relationships. Informed by transportation managers with 15+ years experience. Includes scorecarding frameworks, RFP processes, market intelligence, and compliance vetting. Use when managing carriers, negotiating rates, evaluating carrier performance, or building freight strategies.

    Also in 6 projects that use this

  • TironFoxSkill

    agent-payment-x402

    Add x402 payment execution to AI agents — per-task budgets, spending controls, and non-custodial wallets via MCP tools. Use when agents need to pay for APIs, services, or other agents.

    Also in 4 projects that use this

  • Yog-SothoSkill

    pytorch-patterns

    PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading. Always activate when the user is writing PyTorch models or training scripts, reviewing deep learning code, debugging training loops or data pipelines, optimizing GPU memory or training speed, setting up reproducible experiments, implementing transfer learning or fine-tuning, or asks anything about nn.Module, DataLoader, autograd, AMP, or torch.compile.

    Also in 8 projects that use this

  • +4 more from junimnjw

The file

Create a free account to mount

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free