Designing Tests
CloudAI-X/claude-workflow-v2
Designs and implements testing strategies for any codebase. An agent skill from CloudAI-X/claude-workflow-v2.
Generate, execute, and analyze tests for codebases, covering unit, integration, and end-to-end testing with coverage reporting.
$ npx skills add seb1n/awesome-ai-agent-skills --skill testing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills testing --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/code-and-development/testing .claude/skills/testing && rm -rf skills-srcUse ~/.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/
Install the "testing" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/testing into .claude/skills/testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "testing", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/testingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add seb1n/awesome-ai-agent-skills --skill testing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills testing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/code-and-development/testing .agents/skills/testing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "testing" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/testing into .agents/skills/testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "testing", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add seb1n/awesome-ai-agent-skills --skill testing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills testing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/code-and-development/testing .cursor/skills/testing && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "testing" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/testing into .cursor/skills/testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "testing", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/seb1n/awesome-ai-agent-skills.git --path code-and-development/testing--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add seb1n/awesome-ai-agent-skills --skill testing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills testing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/code-and-development/testing .gemini/skills/testing && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "testing" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/testing into .gemini/skills/testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "testing", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install seb1n/awesome-ai-agent-skills testingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add seb1n/awesome-ai-agent-skills --skill testing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/code-and-development/testing .github/skills/testing && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "testing" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/testing into .github/skills/testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "testing", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add seb1n/awesome-ai-agent-skills --skill testing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills testing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/code-and-development/testing .opencode/skills/testing && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "testing" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/testing into .opencode/skills/testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "testing", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
testingGenerate, execute, and analyze tests for codebases, covering unit, integration, and end-to-end testing with coverage reporting.
Testing is an agent skill from seb1n/awesome-ai-agent-skills. Generate, execute, and analyze tests for codebases, covering unit, integration, and end-to-end testing with coverage reporting. Use when the user requests testing or provides relevant inputs for this workflow.
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Testing & QA, covering Unit testing and End-to-end testing. It works with Jest and pytest. The repository describes itself as: 103 ready-to-use AI agent skills for Claude Code, OpenAI Codex, Gemini CLI, Cursor, GitHub Copilot, Windsurf, and other Agent Skills-compatible tools. Complete SKILL.md… The licence is MIT.
6 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 75865a5. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
pytestnpxjestmvngocargoFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Testing loads about 2.3k tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 773 words of instructions outside code blocks.
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.
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.
The full file from seb1n/awesome-ai-agent-skills at commit 75865a5, republished under its MIT licence (© seb1n). 773 words, ~2,305 tokens.
.claude/skills/testing/SKILL.md (or your agent's skills folder).This skill enables an AI agent to systematically generate, run, and evaluate tests for a given codebase. It covers the full testing lifecycle — from analyzing source code and identifying meaningful test cases, through writing and executing tests, to measuring coverage and recommending improvements. The agent supports unit tests, integration tests, and end-to-end tests across multiple languages and frameworks.
Analyze the source code. Read the target file or module and build a dependency graph of its functions, classes, and external interactions. Identify public interfaces, internal helpers, input parameters, return types, and side effects. This step determines what is testable and what kinds of tests are appropriate.
Identify test cases. For each function or method, enumerate the scenarios that need coverage: happy-path inputs, boundary values, invalid or null inputs, exception paths, and state transitions. For integration points, identify the collaborators that need to be mocked or stubbed versus tested live. Prioritize cases by risk — complex branching logic and public API surfaces come first.
Write the tests. Generate well-structured test code using the project's existing test framework (e.g., pytest, Jest, JUnit). Each test should have a descriptive name that states the scenario and expected outcome. Use the Arrange-Act-Assert pattern: set up preconditions, invoke the code under test, and assert the expected result. Add parameterized tests where a single logical case applies to multiple input sets.
Run the tests. Execute the test suite using the appropriate runner command. Capture the full output including pass/fail status, assertion messages, and timing information. If any tests fail, parse the failure output to determine whether the failure indicates a bug in the source code or an error in the test itself.
Analyze coverage. Run the test suite with coverage instrumentation enabled (e.g., pytest --cov, jest --coverage). Parse the coverage report to identify uncovered lines, branches, and functions. Flag any critical code paths — error handlers, security checks, data validation — that lack coverage.
Suggest improvements. Based on coverage gaps and code complexity, recommend additional test cases. Suggest refactoring opportunities that would make the code more testable, such as extracting pure functions or introducing dependency injection. Provide a summary report with coverage percentages and a prioritized list of next actions.
| Language | Framework | Runner Command |
|---|---|---|
| Python | pytest | pytest --cov=src -v |
| JavaScript | Jest | npx jest --coverage --verbose |
| TypeScript | Jest / Vitest | npx vitest run --coverage |
| Java | JUnit 5 | mvn test |
| Go | testing (stdlib) | go test -cover ./... |
| Rust | cargo test | cargo test |
Provide one or more of the following inputs:
src/utils/parser.py).Given this source file src/cart.py:
class ShoppingCart:
def __init__(self):
self.items = []
def add_item(self, name: str, price: float, quantity: int = 1):
if price < 0:
raise ValueError("Price cannot be negative")
if quantity < 1:
raise ValueError("Quantity must be at least 1")
self.items.append({"name": name, "price": price, "quantity": quantity})
def total(self) -> float:
return sum(item["price"] * item["quantity"] for item in self.items)
def remove_item(self, name: str):
self.items = [item for item in self.items if item["name"] != name]The agent generates tests/test_cart.py:
import pytest
from src.cart import ShoppingCart
@pytest.fixture
def cart():
return ShoppingCart()
def test_add_item_and_total(cart):
cart.add_item("Widget", 9.99, 2)
assert cart.total() == pytest.approx(19.98)
def test_empty_cart_total_is_zero(cart):
assert cart.total() == 0.0
def test_add_item_negative_price_raises(cart):
with pytest.raises(ValueError, match="Price cannot be negative"):
cart.add_item("Bad", -1.0)
def test_add_item_zero_quantity_raises(cart):
with pytest.raises(ValueError, match="Quantity must be at least 1"):
cart.add_item("Bad", 5.0, 0)
def test_remove_item(cart):
cart.add_item("A", 1.0)
cart.add_item("B", 2.0)
cart.remove_item("A")
assert cart.total() == 2.0
def test_remove_nonexistent_item_does_nothing(cart):
cart.add_item("A", 1.0)
cart.remove_item("Z")
assert cart.total() == 1.0Run: pytest tests/test_cart.py --cov=src -v
Given this source file src/validator.js:
function isValidEmail(email) {
if (typeof email !== "string") return false;
const re = /^[^\s@]+@[^\s@]+\.[^\s@]+$/;
return re.test(email);
}
function isStrongPassword(password) {
if (typeof password !== "string") return false;
return (
password.length >= 8 &&
/[A-Z]/.test(password) &&
/[a-z]/.test(password) &&
/[0-9]/.test(password)
);
}
module.exports = { isValidEmail, isStrongPassword };The agent generates src/__tests__/validator.test.js:
const { isValidEmail, isStrongPassword } = require("../validator");
describe("isValidEmail", () => {
test.each([
["user@example.com", true],
["name+tag@sub.domain.org", true],
["missing-at-sign.com", false],
["@no-local.com", false],
["spaces in@email.com", false],
["", false],
])("isValidEmail(%s) => %s", (input, expected) => {
expect(isValidEmail(input)).toBe(expected);
});
test("returns false for non-string input", () => {
expect(isValidEmail(null)).toBe(false);
expect(isValidEmail(42)).toBe(false);
});
});
describe("isStrongPassword", () => {
test("accepts a strong password", () => {
expect(isStrongPassword("Str0ngPwd")).toBe(true);
});
test("rejects short password", () => {
expect(isStrongPassword("Ab1")).toBe(false);
});
test("rejects password without uppercase", () => {
expect(isStrongPassword("alllower1")).toBe(false);
});
test("rejects non-string input", () => {
expect(isStrongPassword(undefined)).toBe(false);
});
});Run: npx jest --coverage --verbose
test_empty_cart_total_is_zero rather than test_total_method. This makes failures self-documenting.@pytest.mark.parametrize or test.each instead of duplicating test bodies.pytest-asyncio, Jest's async handling). The agent will use the appropriate pattern but may ask for confirmation on timeout thresholds.© seb1n, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in code-and-development/testing of seb1n/awesome-ai-agent-skills.
Open the folder on GitHubat commit 75865a5
Testing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Testing this skillseb1n/awesome-ai-agent-skills | 206 | — | ~2.3k | Automated safety check: Pass | MIT | |
| Designing TestsCloudAI-X/claude-workflow-v2 | 1.4k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| E2E Agent Browserjh941213/my-cc-harness | 126 | — | ~3.1k | Automated safety check: Notes | None | |
| Test Detectdavila7/claude-code-templates | 32k | — | ~989 | Automated safety check: Pass | MIT | |
| Error Explanation GeneratorArabelaTso/Skills-4-SE | 253 | — | ~3.8k | Automated safety check: Pass | Apache-2.0 | |
| Discover Testingrand/cc-polymath | 181 | — | ~513 | Automated safety check: Pass | MIT |
CloudAI-X/claude-workflow-v2
Designs and implements testing strategies for any codebase. An agent skill from CloudAI-X/claude-workflow-v2.
jh941213/my-cc-harness
E2E test automation using agent-browser CLI. An agent skill from jh941213/my-cc-harness.
davila7/claude-code-templates
Auto-detect testing framework and run relevant tests. An agent skill from davila7/claude-code-templates.
ArabelaTso/Skills-4-SE
Explains test failures and provides actionable debugging guidance.
rand/cc-polymath
Automatically discover testing skills when working with unit testing, integration testing, e2e testing, TDD, test coverage, mocking, pytest, Jest, or test automation.
jh941213/my-cc-harness
agent-browser CLI를 활용한 E2E 테스트 자동화. An agent skill from jh941213/my-cc-harness.
seb1n/awesome-ai-agent-skills
Plan, execute, document, and retest authorized security assessments of AI agents and multi-agent workflows using safe adversarial cases, synthetic identities, canaries, and evidence-based findings.
seb1n/awesome-ai-agent-skills
Build a preliminary, evidence-based EU AI Act readiness assessment across AI-system inventory, territorial scope, operator roles, prohibited-practice screening, risk classification, transparency…
seb1n/awesome-ai-agent-skills
Design and verify auditable human oversight, approval gates, escalation paths, and safe state transitions for AI agent workflows.
seb1n/awesome-ai-agent-skills
Design, implement, harden, and verify Model Context Protocol (MCP) servers with precise tool contracts, least-privilege authorization, safe transports, structured errors, and interoperability tests.
seb1n/awesome-ai-agent-skills
Inspect, extract, OCR, create, merge, split, reorder, rotate, annotate, fill, redact, compress, secure, and verify PDF documents while preserving source files and visual fidelity.
seb1n/awesome-ai-agent-skills
Audit agent skills, plugins, prompts, manifests, scripts, dependencies, and bundled assets for provenance, prompt-injection, permission, execution, exfiltration, persistence, and update risk.
Categories
Generate, execute, and analyze tests for codebases, covering unit, integration, and end-to-end testing with coverage reporting. Testing is an agent skill from seb1n/awesome-ai-agent-skills. Generate, execute, and analyze tests for codebases, covering unit, integration, and end-to-end testing with coverage reporting.
Testing fits situations like: the user requests testing; provides relevant inputs for this workflow.
Run `npx skills add seb1n/awesome-ai-agent-skills --skill testing -a claude-code`. Or copy the skill folder (code-and-development/testing in seb1n/awesome-ai-agent-skills) into .claude/skills/testing in your project. Claude Code loads it when a task matches its description.
Run `npx skills add seb1n/awesome-ai-agent-skills --skill testing -a codex`. Or copy the skill folder (code-and-development/testing in seb1n/awesome-ai-agent-skills) into .agents/skills/testing in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add seb1n/awesome-ai-agent-skills --skill testing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/testing, .gemini/skills/testing, .github/skills/testing and .opencode/skills/testing in your project.
Going by SKILL.md and its folder, Testing needs the command-line tools its instructions call (pytest, npx, jest, mvn, go and cargo). Our summary lists: Python 3; Node.js.
SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
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.
Testing is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.3k tokens (SKILL.md is roughly 9.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Testing: Designing Tests (CloudAI-X/claude-workflow-v2, 1.4k stars), E2E Agent Browser (jh941213/my-cc-harness, 126 stars), Test Detect (davila7/claude-code-templates, 32k stars) and Error Explanation Generator (ArabelaTso/Skills-4-SE, 253 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
seb1n (a GitHub user) maintains it in seb1n/awesome-ai-agent-skills, which has 206 GitHub stars. The repository holds 92 skills in this directory. The repository was last updated on August 9, 2026.
Source: seb1n/awesome-ai-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.