Official agent skill

Test Smell Detection

by microsoft in microsoft/testfx

Deep-dive audit using the full testsmells.org 19-smell academic catalog for tests in any language.

OfficialMITAuto-check passedTesting & QA

Install Test Smell Detection

skills CLI
$ npx skills add microsoft/testfx --skill test-smell-detection -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install microsoft/testfx test-smell-detection --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/microsoft/testfx.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/test-smell-detection .claude/skills/test-smell-detection && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
test-smell-detection
GitHub stars
1k
Token cost
~5.3k tokens
SKILL.md length
2,351 words
Files
2 (incl. references)
Skills in repo
44
Repo updated
First seen
Licence
MIT

At a glance

Deep-dive audit using the full testsmells.org 19-smell academic catalog for tests in any language.

  • Works in 5 steps: Detect language and load extension → Gather the test code → Scan for test smells → …
  • Pragmatic audits — use test-anti-patterns
  • SKILL.md covers Why Test Smells Matter, When to Use, When Not to Use and Inputs, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Test Smell Detection is an agent skill from microsoft/testfx, published by the product's own GitHub organization. Deep-dive audit using the full testsmells.org 19-smell academic catalog for tests in any language. Every finding maps to a named, citable smell from the research literature (Assertion Roulette, Duplicate Assert, Mystery Guest, Eager Test, Sensitive Equality, Conditional Test Logic, Sleepy Test, Magic Number Test, etc.) with research-backed severity. Polyglot: .NET (MSTest/xUnit/NUnit/TUnit), Python (pytest/unittest), TS/JS (Jest/Vitest/Mocha/node:test), Java (JUnit/TestNG), Go, Ruby (RSpec/Minitest), Rust, Swift…

Its SKILL.md is about 5.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/test-smell-catalog.md`).

It sits in Testing & QA, covering Unit testing. It works with JUnit, Jest, pytest and Vitest. The repository describes itself as: This repository holds the source code of Microsoft.Testing.Platform (MTP), a lightweight alternative to VSTest, as well as MSTest adapter and framework. The licence is MIT.

When your agent uses it

  • Pragmatic audits — use test-anti-patterns
  • Writing new tests (use code-testing-agent
  • Writing-mstest-tests for MSTest)
  • Running tests (use run-tests)

Example prompts

  • “/test-smell-detection”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Detect language and load extension
  2. Gather the test code
  3. Scan for test smells
  4. Apply calibration rules
  5. Report findings

What it can do on your machine

Read from SKILL.md and the folder at commit 44b9dcc. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Test Smell Detection loads about 5.3k tokens when it runs, and up to ~6.8k if it reads all its reference files. Until then it costs about 234 tokens; SKILL.md has 2,351 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~234
When it runs · the whole SKILL.md, loaded when a task matches
~5.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from microsoft/testfx at commit 44b9dcc, republished under its MIT licence (© microsoft). 2,351 words, ~5,299 tokens.

Download SKILL.mdSave it as .claude/skills/test-smell-detection/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
test-smell-detection
description
Deep-dive audit using the full testsmells.org 19-smell academic catalog for tests in any language. Every finding maps to a named, citable smell from the research literature (Assertion Roulette, Duplicate Assert, Mystery Guest, Eager Test, Sensitive Equality, Conditional Test Logic, Sleepy Test, Magic Number Test, etc.) with research-backed severity. Polyglot: .NET (MSTest/xUnit/NUnit/TUnit), Python (pytest/unittest), TS/JS (Jest/Vitest/Mocha/node:test), Java (JUnit/TestNG), Go, Ruby (RSpec/Minitest), Rust, Swift, Kotlin (JUnit/Kotest), PowerShell (Pester), C++ (GoogleTest/Catch2). INVOKE ONLY when explicitly asked for the testsmells.org 19-smell academic catalog or citable smell names from the literature. DO NOT USE FOR: general or pragmatic audits — use test-anti-patterns; writing new tests (use code-testing-agent, or writing-mstest-tests for MSTest); running tests (use run-tests); framework migration.
license
MIT

Test Smell Detection

Deep formal audit of test code in any supported language using an academic test smell taxonomy. Detects symptoms of bad design or implementation decisions that make tests harder to understand, more fragile, less effective at catching bugs, or more expensive to maintain. Produces a severity-ranked report with specific locations and actionable fixes.

Language-specific guidance: Call the test-analysis-extensions skill to discover available extension files, then read the file matching the target codebase. The extension file documents test markers, sleep / time / random APIs, skip annotations, setup/teardown, mystery-guest indicators (file/database/network/env), integration markers, and language-specific calibration notes that drive the smell detectors below.

Why Test Smells Matter

Test smells erode confidence in a test suite and inflate maintenance costs:

ProblemConsequence
Tests with conditional logicSome paths never execute — hidden testing gaps
Tests that depend on external resourcesFlaky failures, slow execution, environment coupling
Tests that sleep to wait for resultsNon-deterministic timing, slow suites, false failures
Tests without assertionsFalse confidence — coverage looks good but nothing is verified
Tests that call many production methodsHard to diagnose failures, unclear what's being tested
Tests with magic numbersUnreadable intent, unclear boundary conditions
Tests relying on ToString for comparisonBrittle to formatting changes, obscure failure messages
Tests with exception handling logicSwallowed failures, tests that pass when they shouldn't

When to Use

  • User asks for a comprehensive or formal test smell audit
  • User asks "are my tests well-written?" and wants a thorough analysis
  • User wants a test quality health check with academic rigor
  • User asks for a review of test design or structure using standard smell categories
  • User suspects tests are fragile, flaky, or giving false confidence and wants a deep investigation

When Not to Use

  • User wants a quick pragmatic test review (use test-anti-patterns — faster, covers the most common issues)
  • User wants to evaluate assertion diversity specifically (use assertion-quality)
  • User wants to find duplicated boilerplate across tests (use exp-test-maintainability)
  • User wants to write new tests from scratch (help them directly)
  • User wants to fix a specific failing test (diagnose and fix directly)

Inputs

InputRequiredDescription
Test codeYesOne or more test files or a test project directory to analyze
Production codeNoThe code under test, for context on whether patterns are justified

Workflow

Step 1: Detect language and load extension

Identify the target codebase's language and test framework. Call the test-analysis-extensions skill and read the matching extension file (e.g., extensions/dotnet.md, extensions/python.md, extensions/typescript.md, extensions/go.md). The extension file lists the framework-specific test markers, sleep / wait APIs, skip / ignore attributes, mystery-guest indicators, and integration-test markers that the smell detectors below need.

Step 2: Gather the test code

Read all test files the user provides. If the user points to a directory or project, scan for all test files using the markers in the loaded language extension file.

For a thorough audit, also consult the extended smell catalog which covers 9 additional smell types beyond the core 10 below.

Step 3: Scan for test smells

For each test method and class, check for the following smell categories. Examples reference .NET attributes but the patterns apply across all supported languages — use the loaded language extension file to map each pattern to the framework you are auditing.

Smell 1: Conditional Test Logic

Test methods containing if, else, switch, ternary (? :), for, foreach, while, or pattern-match arms that change assertion behavior. Control flow in tests means some paths may never execute, hiding gaps.

Severity: High Detection: Any control-flow statement inside a test method body that affects which assertions run. Exceptions (per-language idioms, do NOT flag):

  • Foreach-assert used solely to assert every item in a known collection (the assertion is the loop body).
  • Go / Rust table-driven tests: for _, tt := range tests { t.Run(tt.name, func(t *testing.T) { ... }) } (Go) or #[rstest] parametrized loops are idiomatic.
  • it.each(...) / test.each(...) / @pytest.mark.parametrize / [Theory] + [InlineData] / @ParameterizedTest parametrization driven by data tables.
  • Pester -ForEach / -TestCases and RSpec where blocks.
  • Catch2 SECTIONs and GENERATE(...), doctest SUBCASE, GoogleTest INSTANTIATE_TEST_SUITE_P.
Smell 2: Mystery Guest

Tests that depend on external resources — files on disk, databases, network endpoints, environment variables — without making the dependency explicit or using test doubles.

Severity: High Detection: Test methods that read files, open database connections, make HTTP requests (without a test handler), read environment variables, or use hard-coded file paths. Per language: File.ReadAllText / Directory.GetFiles / HttpClient / Environment.GetEnvironmentVariable (.NET); open() / pathlib.Path.read_text() / requests.get() / os.environ[...] (Python); fs.readFileSync / fetch(...) / process.env.X (JS/TS); Files.readAllBytes / Files.newInputStream / HttpClient.send / System.getenv (Java); os.ReadFile / http.Get / os.Getenv (Go); File.read / Net::HTTP.get / ENV[...] (Ruby); std::fs::read_to_string / reqwest::get / std::env::var (Rust); String(contentsOfFile:) / URLSession.shared.data / ProcessInfo.processInfo.environment (Swift); File(...).readText() / URL(...).openConnection() / System.getenv (Kotlin); Get-Content / Invoke-WebRequest / $env:X (Pester); std::ifstream / curl_easy_perform / std::getenv (C++). Exception: In-memory fakes, test-specific handlers, or hermetic test data factories are fine.

Smell 3: Sleepy Test

Tests that call sleep or delay functions to wait for a condition. These introduce non-deterministic timing and slow down the suite.

Severity: High Detection: Calls to sleep/delay functions inside test methods: Thread.Sleep / Task.Delay (.NET); time.sleep / asyncio.sleep (Python); setTimeout / await new Promise(r => setTimeout(...)) / jest.advanceTimersByTime not paired with a wait (JS/TS); Thread.sleep / TimeUnit.SECONDS.sleep (Java); time.Sleep (Go); sleep / Kernel#sleep (Ruby); std::thread::sleep / tokio::time::sleep (Rust); Thread.sleep / delay (Kotlin coroutines); sleep(_:) / Task.sleep (Swift); Start-Sleep (Pester); std::this_thread::sleep_for (C++). See the matching language extension file for the full list.

Smell 4: Assertion-Free Test (Unknown Test)

Tests that execute code but never assert anything. Test frameworks report these as passing even if the code is completely broken, as long as no exception is thrown.

Severity: High Detection: A test method with no assertion calls and no expected-exception annotation. Framework-specific: missing Assert.* (.NET); no assert / pytest.raises (Python); no expect(...) or assert.* (JS/TS); no assert* / assertThat (Java); no t.Error* / t.Fatal* / assert.* testify (Go); no expect/.to/.eq (RSpec) or assert*/refute* (Minitest); no assert*! / assert_eq! / panic! (Rust); no XCTAssert* / #expect (Swift); no assert* / should* / Kotest matchers (Kotlin); no Should -* (Pester); no EXPECT_* / ASSERT_* / REQUIRE / CHECK (C++). Calibration:

  • A method named *_DoesNotThrow / *_no_exception / should not throw is implicitly asserting no exception — still flag it but note it may be intentional.
  • Mock-call verifications count as assertions: mock.Verify(...) (Moq), Mock.AssertWasCalled (NSubstitute), mock.assert_called_with(...) (Python), expect(mock).toHaveBeenCalledWith(...) (Jest), verify(mock).method(...) (Mockito), Should -Invoke (Pester) — do NOT flag tests using these as assertion-free.
  • Bare assertion forms count: assert x == y (pytest), if got != want { t.Errorf(...) } (Go), assert!(cond) (Rust) are canonical.
  • Snapshot assertions count: .toMatchSnapshot() (Jest), syrupy (pytest), SnapshotTesting (Swift), approval-tests are real assertions.
  • Missing await on async assertions is its own critical smell: expect(promise).resolves.toBe(x) without await/return (Jest), un-awaited Assert.ThrowsAsync (xUnit), un-awaited coroutines in pytest-asyncio, Kotest tests without runTest, Swift Testing async cases without await. These tests have assertion calls but silently pass — flag with a dedicated note.
Smell 5: Eager Test

A test method that calls many different production methods, making it unclear what behavior is being tested. When it fails, diagnosis is difficult because the failure could stem from any of the calls.

Severity: Medium Detection: A test method that calls 4+ distinct methods on the production object (excluding setup/construction). Count unique method names, not call count. Calibration: Integration / end-to-end / workflow tests may legitimately call multiple methods. Check for integration markers in the loaded language extension file (e.g., [Trait("Category", "Integration")], @Tag("integration"), pytest.mark.integration, *_integration_test.go, Describe ... -Tag 'Integration') and downgrade.

Smell 6: Magic Number Test

Assertions that contain unexplained numeric literals. The intent of Assert.AreEqual(42, result) / assert result == 42 / expect(result).toBe(42) is unclear without context — what does 42 represent?

Severity: Medium Detection: Numeric literals (other than 0, 1, -1, and the literal used in the test name) appearing as expected parameters in assertion methods or comparison operands. Calibration: Small integers in context (like count checks Assert.AreEqual(3, list.Count) / assert len(items) == 3 / expect(arr.length).toBe(3) where 3 items were just added) are acceptable — only flag when the number's meaning is genuinely unclear.

Smell 7: Sensitive Equality

Tests that use string conversion for comparison or assertion. If the underlying string representation changes, the test breaks even though the actual behavior is correct.

Severity: Medium Detection: Assert.AreEqual(expected, obj.ToString()) (.NET); assert str(obj) == "..." or assert repr(obj) == "..." (Python); expect(obj.toString()).toBe("...") or expect(${obj}).toBe(...) (JS/TS); assertEquals(expected, obj.toString()) (Java); assert.Equal(t, "...", fmt.Sprint(obj)) or obj.String() chains (Go); expect(obj.to_s).to eq("...") (RSpec); assert_eq!(format!("{}", obj), "...") or assert_eq!(format!("{:?}", obj), "...") (Rust); XCTAssertEqual(obj.description, "...") or string-interpolation assertion (Swift); assertEquals("...", obj.toString()) (Kotlin); Should -Be "..." against a [string]$obj (Pester); EXPECT_EQ("...", std::to_string(obj)) (C++).

Smell 8: Exception Handling in Tests

Tests that contain try/catch/except/rescue blocks or throw/raise/panic/return err statements used to manage exception flow instead of asserting on it. This typically means the test is manually managing errors rather than using the framework's built-in exception assertion facilities.

Severity: Medium Detection: try/catch (.NET, Java, JS/TS, Kotlin, Swift, C++); try/except (Python); begin/rescue (Ruby); defer recover() (Go); manual if err != nil { t.Fatal(err) } in Go is canonical and NOT a smell. Exception: catch/except/rescue blocks that capture an exception for further assertion on its properties are a lesser concern — note but don't flag as high severity.

Show full SKILL.md (939 more words)Show less
Smell 9: General Fixture (Over-broad Setup)

The test setup method, constructor, or fixture initializes fields that are not used by every test method. This means each test pays the cost of setting up objects it doesn't need.

Severity: Low Detection: Fields/properties initialized in [TestInitialize] / setUp / @BeforeEach / beforeEach / before(:each) / BeforeEach (Pester) / setUpWithError (XCTest) / pytest fixture(autouse=True) / xUnit constructor / Kotest beforeTest that are referenced by fewer than half the test methods in the class/module/file.

Smell 10: Ignored / Disabled / Skipped Test

Tests marked as skipped or disabled. These add overhead and clutter, and the underlying issue they were disabled for may never be addressed.

Severity: Low Detection: Skip / ignore / disable annotations or conditional compilation that disables a test. See the loaded language extension file for framework-specific skip attributes — e.g., [Ignore] (MSTest/NUnit), Skip = "..." (xUnit Fact), @Ignore (TUnit/JUnit 4), @Disabled (JUnit 5), @pytest.mark.skip / pytest.skip(...) / pytestmark, it.skip / xit / describe.skip / test.skip (Jest/Vitest/Mocha), t.Skip(...) (Go), pending / skip / xit (RSpec), #[ignore] (Rust), XCTSkip / @Test(.disabled) (Swift), @Ignored (Kotest), -Skip (Pester), GTEST_SKIP() / DISABLED_TestName (GoogleTest), [.] tag (Catch2), TEST_CASE("...", "[.]") skip.

Step 4: Apply calibration rules

Before reporting, calibrate findings to avoid false positives:

  • Integration tests have different norms. A test class clearly marked as integration (by name, annotation, category, or convention — see the loaded language extension file for markers) legitimately uses external resources, calls multiple methods, and may use delays for async coordination. Downgrade Mystery Guest, Eager Test, and Sleepy Test severity for integration tests — note them but don't flag as problems.
  • Simple loop-assert patterns are fine. Iterating a collection to assert on every item is readable and correct. Only flag loops with complex branching logic.
  • Idiomatic table-driven and parametrized patterns are NOT Conditional Test Logic. Go's for _, tt := range tests { t.Run(...) }, Rust's #[rstest], pytest's @parametrize, Jest/Vitest .each, JUnit @ParameterizedTest, RSpec where, Pester -ForEach, Catch2 SECTION/GENERATE, GoogleTest INSTANTIATE_TEST_SUITE_P are canonical and must NOT be flagged.
  • Context matters for magic numbers. A count assertion right after adding a known number of items is self-documenting. Only flag numbers whose meaning requires looking at production code to understand.
  • Bare assert (pytest) is canonical, not assertion-free framework use. Don't flag.
  • Go's if err != nil { t.Fatal(err) } is canonical, not Exception Handling in Tests. Don't flag.
  • Mock-call verifications and snapshot assertions are real assertions — do not flag tests using them as Assertion-Free.
  • Missing-await on async assertions is its own critical sub-smell of Assertion-Free — these tests silently pass even when the underlying assertion fails. Always flag when detected.
  • Inconclusive/pending markers are not assertion-free. Tests explicitly marked as incomplete should be flagged as Ignored Test, not Assertion-Free.
  • Capture-and-assert exception patterns are borderline. try { ... } catch (X x) { Assert.Equal(...) } style patterns are ugly but functional. Note as a smell and suggest the framework's built-in exception assertion (Assert.Throws<T>, pytest.raises, expect(fn).toThrow, assertThrows, assert.PanicsWithError, etc.) instead of calling it broken.
  • If the test suite is clean, say so. A report finding few or no smells is perfectly valid.
Step 5: Report findings

Present the analysis in this structure:

  1. Summary Dashboard — Quick overview:

    | Severity | Smell Count | Affected Tests |
    |----------|-------------|----------------|
    | High     | 3           | 7              |
    | Medium   | 2           | 4              |
    | Low      | 1           | 2              |
    | Total    | 6           | 13             |
  2. Findings by Severity — For each smell found:

    • Smell name and category
    • Severity level with rationale
    • Affected test methods (file and method name)
    • Code snippet showing the smell
    • Concrete fix: show what the code should look like after remediation
    • Risk if left unfixed
  3. Smell-Free Patterns — If any test methods are well-written, briefly acknowledge this. Highlighting what's good helps the user understand the contrast.

  4. Prioritized Remediation Plan — Rank fixes by:

    • Impact (high-severity smells affecting many tests first)
    • Effort (quick fixes before refactoring)
    • Risk (fixes that prevent false-passes before cosmetic improvements)

Validation

  • Every finding includes the specific test method name and file location
  • Every finding includes a code snippet showing the smell in context
  • Every finding includes a concrete fix example (not just "fix this")
  • Integration tests are not penalized for patterns that are appropriate for their scope
  • Simple foreach-assert loops are not flagged as conditional test logic
  • Contextually obvious numbers are not flagged as magic numbers
  • If the test suite is clean, the report says so upfront
  • Severity levels are justified, not arbitrary

Common Pitfalls

PitfallSolution
Flagging integration tests for using real resourcesCheck for integration test markers (per the loaded language extension) and adjust severity accordingly
Flagging loop-over-collection-assert as conditional logicOnly flag loops with branching or complex logic, not assertion iterations
Flagging Go/Rust table-driven loops as Conditional Test Logicfor _, tt := range tests { t.Run(...) } (Go) and #[rstest] loops (Rust) are canonical and must NOT be flagged
Flagging parametrized tests as Duplicate Assert@pytest.mark.parametrize, it.each, [Theory]+[InlineData], @ParameterizedTest, RSpec where, Pester -ForEach, Catch2 SECTION/GENERATE are correct deduplication, not smells
Flagging pytest bare assert as missing frameworkBare assert is canonical pytest assertion — count it
Flagging Go's if err != nil { t.Fatal(err) } as Exception Handling in TestsThis is canonical Go error checking — do NOT flag
Flagging obvious count assertions after adding N itemsConsider the immediate context — self-documenting numbers are fine
Missing framework-specific assertion syntaxAlways read the matching language extension file first; each framework has distinct assertion APIs (xUnit Assert.Equal, MSTest Assert.AreEqual, NUnit Is.EqualTo, pytest bare assert, Jest expect().toBe(), etc.)
Treating mock-call verifications as assertion-freemock.Verify(...), expect(mock).toHaveBeenCalledWith(...), Should -Invoke, verify(mock).method(...), mock.assert_called_with(...) are real assertions
Missing the async-test silent-pass trapAlways flag expect(promise).resolves.toBe(x) without await/return, un-awaited Assert.ThrowsAsync (xUnit), un-awaited coroutines in pytest-asyncio, missing runTest in Kotest, un-awaited Swift Testing async assertions
Over-flagging try/catch that captures for assertionDistinguish swallowed exceptions from capture-and-assert patterns
Treating skip annotations with reasons same as bare skipsNote that reasoned skips (Skip = "Tracked by #123", @pytest.mark.skip(reason="..."), t.Skip("not yet implemented")) are less concerning than unexplained ones
Flagging DoesNotThrow-style tests as assertion-freeThese implicitly assert no exception — note but acknowledge the intent

© microsoft, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in .agents/skills/test-smell-detection of microsoft/testfx.

  • SKILL.md
  • references/test-smell-catalog.md

Open the folder on GitHubat commit 44b9dcc

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Categories

Questions about Test Smell Detection

What does Test Smell Detection do?

Deep-dive audit using the full testsmells.org 19-smell academic catalog for tests in any language. Test Smell Detection is an agent skill from microsoft/testfx, published by the product's own GitHub organization.org 19-smell academic catalog for tests in any language.

When should I use Test Smell Detection?

Test Smell Detection fits situations like: pragmatic audits — use test-anti-patterns; writing new tests (use code-testing-agent; writing-mstest-tests for MSTest); running tests (use run-tests).

How do I install Test Smell Detection in Claude Code?

Run `npx skills add microsoft/testfx --skill test-smell-detection -a claude-code`. Or copy the skill folder (.agents/skills/test-smell-detection in microsoft/testfx) into .claude/skills/test-smell-detection in your project. Claude Code loads it when a task matches its description.

How do I install Test Smell Detection in Codex?

Run `npx skills add microsoft/testfx --skill test-smell-detection -a codex`. Or copy the skill folder (.agents/skills/test-smell-detection in microsoft/testfx) into .agents/skills/test-smell-detection in your project. Codex loads it when a task matches its description.

Can I use Test Smell Detection in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft/testfx --skill test-smell-detection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/test-smell-detection, .gemini/skills/test-smell-detection, .github/skills/test-smell-detection and .opencode/skills/test-smell-detection in your project.

What does Test Smell Detection need to run?

SKILL.md names no scripts, command-line tools or credentials: Test Smell Detection is instructions for the agent only. Our summary lists: Python 3.

Does Test Smell Detection access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Test Smell Detection safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Test Smell Detection use?

Test Smell Detection is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Test Smell Detection use?

About 5.3k tokens (SKILL.md is roughly 21k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.5k tokens, read only when the agent opens those files.

What are the alternatives to Test Smell Detection?

Skills that share tags, products or a category with Test Smell Detection: TDD Guide (LeoYeAI/openclaw-master-skills, 2.2k stars), Interval Guided Regression Test Update (ArabelaTso/Skills-4-SE, 253 stars), TDD Guide (alirezarezvani/claude-skills, 28k stars) and TDD Guide (borghei/Claude-Skills, 874 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Test Smell Detection?

microsoft (a GitHub organization, an official publisher) maintains it in microsoft/testfx, which has 1,047 GitHub stars. The repository holds 44 skills in this directory. The repository was last updated on October 7, 2026.

Source: microsoft/testfx on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.