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 KunanonJ/ai-skills-hub --skill unit-testing-test-generategit clone --depth 1 https://github.com/KunanonJ/ai-skills-hubWrote 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/kunanonj/ai-skills-hub/unit-testing-test-generate)<a href="https://agentmods.dev/skills/kunanonj/ai-skills-hub/unit-testing-test-generate"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/unit-testing-test-generate/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/kunanonj/ai-skills-hub/unit-testing-test-generate"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/unit-testing-test-generate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00023 | $0.02482 |
| Opus 5 | $0.00012 | $0.01241 |
| Sonnet 5 | $0.00005 | $0.00496 |
| Haiku 4.5 | $0.00002 | $0.00248 |
Grade A, and why
unit-testing-test-generate scanned grade A with 1 finding 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 6d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run( This is a copy
88% identical to unit-testing-test-generate — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 328 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Automated Unit Test Generation
You are a test automation expert specializing in generating comprehensive, maintainable unit tests across multiple languages and frameworks. Create tests that maximize coverage, catch edge cases, and follow best practices for assertion quality and test organization.
Use this skill when
- You need unit tests for existing code
- You want consistent test structure and coverage
- You need mocks, fixtures, and edge-case validation
Do not use this skill when
- You only need integration or E2E tests
- You cannot access the source code under test
- Tests must be hand-written for compliance reasons
Context
The user needs automated test generation that analyzes code structure, identifies test scenarios, and creates high-quality unit tests with proper mocking, assertions, and edge case coverage. Focus on framework-specific patterns and maintainable test suites.
Requirements
$ARGUMENTS
Instructions
1. Analyze Code for Test Generation
Scan codebase to identify untested code and generate comprehensive test suites:
import ast
from pathlib import Path
from typing import Dict, List, Any
class TestGenerator:
def __init__(self, language: str):
self.language = language
self.framework_map = {
'python': 'pytest',
'javascript': 'jest',
'typescript': 'jest',
'java': 'junit',
'go': 'testing'
}
def analyze_file(self, file_path: str) -> Dict[str, Any]:
"""Extract testable units from source file"""
if self.language == 'python':
return self._analyze_python(file_path)
elif self.language in ['javascript', 'typescript']:
return self._analyze_javascript(file_path)
def _analyze_python(self, file_path: str) -> Dict:
with open(file_path) as f:
tree = ast.parse(f.read())
functions = []
classes = []
for node in ast.walk(tree):
if isinstance(node, ast.FunctionDef):
functions.append({
'name': node.name,
'args': [arg.arg for arg in node.args.args],
'returns': ast.unparse(node.returns) if node.returns else None,
'decorators': [ast.unparse(d) for d in node.decorator_list],
'docstring': ast.get_docstring(node),
'complexity': self._calculate_complexity(node)
})
elif isinstance(node, ast.ClassDef):
methods = [n.name for n in node.body if isinstance(n, ast.FunctionDef)]
classes.append({
'name': node.name,
'methods': methods,
'bases': [ast.unparse(base) for base in node.bases]
})
return {'functions': functions, 'classes': classes, 'file': file_path}
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.
- 6d ago First seen · 328 lines · 23 tokens per session scan A 3fdc338d79aa
unit-testing-test-generate is a skill published in the GitHub repository KunanonJ/ai-skills-hub (5 stars, last pushed 1mo ago), licensed MIT. It adds 23 tokens to every session and 2,482 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). It is 88% identical to unit-testing-test-generate, differing in 6 lines, and is treated as a copy.
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