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Code Testing Generation

Free

Generate unit tests for various programming languages effortlessly.

by dotnet5.1k stars on dotnet/skills
Updated Aug 10, 2026
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Free · Opens the source repo

What Code Testing Generation does

The Code Testing Generation skill is designed to assist developers in creating unit tests for their codebases across multiple programming languages, including C#, Python, TypeScript/JavaScript, Go, Rust, Java, and Ruby. This skill serves as a mandatory entry point for generating or writing tests, ensuring that developers can efficiently scaffold test projects, improve coverage, and add tests for new or untested code. By invoking this skill before making changes to files, users can streamline their testing workflow and maintain high code quality.

The skill operates through a coordinated multi-agent pipeline that encompasses research, planning, and implementation phases. It begins by analyzing the user's request to determine the appropriate scope, whether for a single function or an entire project. The pipeline is structured to optimize the test generation process, ensuring that the generated tests are comprehensive and adhere to project conventions. The skill not only generates tests that compile and pass but also helps in improving overall test coverage, which is crucial for maintaining robust applications.

This skill is particularly useful for developers who are looking to enhance their testing practices without having to manually write extensive test cases. It automates the process of generating unit tests, allowing developers to focus on writing code rather than on the intricacies of test creation. The inclusion of best practices and guidelines from the bundled prompt file ensures that the generated tests align with industry standards, making it a valuable tool for teams aiming for high-quality software development.

However, this skill is not intended for running existing tests or for debugging failing test logic. It is specifically tailored for generating new tests and improving coverage, making it an ideal choice for developers working on new features or refactoring existing codebases.

When to use it

Invoke this skill when you need to generate unit tests for a project, improve test coverage, or write tests for new features.

When not to use it

Do not use this skill for running existing tests or for debugging test failures; it is specifically for generating new tests.

What you can build with it

Generating Tests for New Features

Use this skill to quickly generate unit tests for newly developed features, ensuring they are covered from the start.

Improving Test Coverage

Invoke this skill to identify and add tests for previously untested code, helping to achieve better overall coverage.

Scaffolding Test Projects

Utilize this skill to scaffold a test project or suite, streamlining the setup process for testing your application.

How to install Code Testing Generation

View source

1. Install with the skills CLI

npx skills add dotnet/skills/code-testing-agent --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by dotnet

Code Testing Generation Skill

An AI-powered skill that generates comprehensive, workable unit tests for any programming language using a coordinated multi-agent pipeline.

When to Use This Skill

Use this skill when you need to:

  • Generate unit tests for an entire project or specific files
  • Improve test coverage for existing codebases
  • Create test files that follow project conventions
  • Write tests that actually compile and pass
  • Add tests for new features or untested code

When Not to Use

  • Running or executing existing tests (use the run-tests skill)
  • Migrating between test frameworks (use migration skills)
  • Writing tests specifically for MSTest patterns (use writing-mstest-tests)
  • Debugging failing test logic

How It Works

This skill coordinates multiple specialized agents in a Research → Plan → Implement pipeline:

Pipeline Overview

┌─────────────────────────────────────────────────────────────┐
│                     TEST GENERATOR                          │
│  Coordinates the full pipeline and manages state            │
└─────────────────────┬───────────────────────────────────────┘
                      │
        ┌─────────────┼─────────────┐
        ▼             ▼             ▼
┌───────────┐  ┌───────────┐  ┌───────────────┐
│ RESEARCHER│  │  PLANNER  │  │  IMPLEMENTER  │
│           │  │           │  │               │
│ Analyzes  │  │ Creates   │  │ Writes tests  │
│ codebase  │→ │ phased    │→ │ per phase     │
│           │  │ plan      │  │               │
└───────────┘  └───────────┘  └───────┬───────┘
                                      │
                    ┌─────────┬───────┼───────────┐
                    ▼         ▼       ▼           ▼
              ┌─────────┐ ┌───────┐ ┌───────┐ ┌───────┐
              │ BUILDER │ │TESTER │ │ FIXER │ │LINTER │
              │         │ │       │ │       │ │       │
              │ Compiles│ │ Runs  │ │ Fixes │ │Formats│
              │ code    │ │ tests │ │ errors│ │ code  │
              └─────────┘ └───────┘ └───────┘ └───────┘

Step-by-Step Instructions

Step 1: Determine the user request

Make sure you understand what user is asking and for what scope. When the user does not express strong requirements for test style, coverage goals, or conventions, source the guidelines from unit-test-generation.prompt.md. This prompt provides best practices for discovering conventions, parameterization strategies, coverage goals (aim for 80%), and language-specific patterns.

Step 2: Size the request before invoking anything

Match the machinery to the scope. Running the full pipeline on a one-file request costs turns and tool calls without improving the tests.

ScopeWhat it looks likeHow to run it
FocusedOne function, class, or file; "tests for X only"; extending an existing suite with the missing casesSkip the .testagent/ artifacts and the sub-agent fan-out. Keep the requirement checklist in your head (or in the final table), read only the target and one neighbouring test for conventions, write the tests, run the narrowest test command, review your own assertions inline.
BroadA project, package, or module set; "comprehensive suite"; a coverage threshold to clear across several filesRun the full Research → Plan → Implement pipeline in Step 3, with the .testagent/ artifacts and the completion contract below.

When in doubt, start focused and escalate only if the request turns out to span several files. Escalating costs one extra pass; running the broad pipeline on a focused request costs several.

Step 3: Invoke the Test Generator (broad scope)

Start by calling the code-testing-generator agent with your test generation request:

Generate unit tests for [path or description of what to test], following the [unit-test-generation.prompt.md](unit-test-generation.prompt.md) guidelines. Treat the current workspace as authoritative even when it is sparse, gutted-looking, synthetic, or missing tracked files; never restore or reconstruct it.

The Test Generator will manage the entire pipeline automatically.

If code-testing-generator is unavailable, do not skip the workflow. Execute the same Research → Plan → Implement sequence inline, create the .testagent/ artifacts described below, and apply the same completion contract.

Step 4: Execute with bounded context

For multi-file requests:

  1. Turn every explicit user requirement into a checklist before implementation. Include requested layers, collaborators to mock, boundary cases, integrations, coverage thresholds, and report artifacts. Copy multi-condition requirements verbatim — they must each map to one test that exercises the whole combination.
  2. Research only the requested module or project and write the checklist plus a compact target inventory to .testagent/research.md.
  3. Reuse manifests, symbol references, and deterministic pairing tools instead of reading every source and test file.
  4. For multi-file scopes in C#, Python, TypeScript/JavaScript, Go, Java, Rust, or Ruby, run find-untested-sources once and consume its pairing and suggested-path output; do not repeat that discovery manually.
  5. Plan each target file once, then implement phases sequentially. Map every checklist item to at least one concrete test or explain why it is blocked.
  6. Build and test the narrow target during fix cycles; run workspace-level validation once at the end.
  7. Before reporting success, re-open the generated tests and verify every checklist item against concrete test names and assertions. Coverage alone is not evidence that a requested mock seam, boundary, state transition, or property combination was tested.
  8. Read a language example from code-testing-extensions only when the repository has no representative tests and the base extension is insufficient.

Completion contract

Every scope must satisfy points 3–5 below. Points 1 and 2 are the broad-scope artifacts: on a focused request the same reasoning happens inline and no .testagent/ files are written.

Do not report completion until all of these are true:

  1. (broad scope) .testagent/research.md records the bounded target inventory, existing test conventions, and the acceptance checklist.
  2. (broad scope) .testagent/plan.md maps each checklist item to a planned test or an explicit blocker.
  3. Generated tests compile and pass with the narrowest relevant test command.
  4. Every explicit user requirement is backed by a concrete test and assertion. Fix missing mock seams, boundary cases, state transitions, and property combinations even when coverage already passes. In the final summary, cite at least one generated test name for every checklist item so completion is auditable; if an item has no test to cite, keep implementing or report it as blocked. For non-behavioral requirements such as scaffolding, scope limits, commands, or coverage artifacts, cite the relevant file, command, or report instead of forcing a test-name mapping.
  5. Review the generated tests for behavior gaps and weak assertions. On a broad scope, invoke test-gap-analysis and assertion-quality when available and record the findings and fixes in .testagent/status.md. On a focused scope, do the equivalent review inline — re-read each generated assertion against the source — without spawning extra passes.

The final response MUST include a compact Requirement | Evidence table. Behavioral rows cite exact generated test names. Non-behavioral rows cite the relevant project file, validation command, or coverage report. A generic list of tested areas is not a substitute for requirement-by-requirement evidence.

Quote the user's requirement verbatim in each row. When the request names a specific combination — "a case where a composite discount, regional tax, and weight-based shipping all apply", "the difference between summed and chained discounts", "constructor validation for every class" — the row must cite the one test that demonstrates exactly that. A test that merely exercises the same collaborators does not satisfy a requirement about their interaction, and per-class requirements need a citation per class.

Cite a clean run, not an attempt. The commands behind the evidence table must have finished successfully: quote the final passing test summary and, when thresholds were requested, the per-module coverage table from a run that exited 0. If the last coverage run exited non-zero, fix it and re-run before reporting; never infer threshold clearance from a failed or partial run.

State Management

Broad-scope runs store pipeline state in the .testagent/ folder. A focused request does not create these files:

FilePurpose
.testagent/research.mdCodebase analysis results
.testagent/plan.mdPhased implementation plan
.testagent/status.mdProgress tracking (optional)

Agent Reference

AgentPurpose
code-testing-generatorCoordinates pipeline
code-testing-researcherAnalyzes codebase
code-testing-plannerCreates test plan
code-testing-implementerWrites test files
code-testing-builderCompiles code
code-testing-testerRuns tests
code-testing-fixerFixes errors
code-testing-linterFormats code

Requirements

  • Project must have a build/test system configured
  • Testing framework should be installed (or installable)
  • VS Code with GitHub Copilot extension

Troubleshooting

Tests don't compile

The code-testing-fixer agent will attempt to resolve compilation errors. Check .testagent/plan.md for the expected test structure. Call the code-testing-extensions skill and read the language-specific extension file for error code references (e.g., dotnet.md for .NET).

Tests fail

Most failures in generated tests are caused by wrong expected values in assertions, not production code bugs:

  1. Read the actual test output
  2. Read the production code to understand correct behavior
  3. Fix the assertion, not the production code
  4. Never mark tests [Ignore] or [Skip] just to make them pass

Wrong testing framework detected

Specify your preferred framework in the initial request: "Generate Jest tests for..."

Environment-dependent tests fail

Tests that depend on external services, network endpoints, specific ports, or precise timing will fail in CI environments. Focus on unit tests with mocked dependencies instead.

Build fails on full solution

During phase implementation, build only the specific test project for speed. After all phases, run a full non-incremental workspace build to catch cross-project errors.

Frequently asked questions about Code Testing Generation

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