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 agentmods add skills/avinashp/agentsatlas/testingnpx skills add AvinashP/AgentsAtlas --skill testinggit clone --depth 1 https://github.com/AvinashP/AgentsAtlasWhat 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 | $0.00028 | $0.01443 |
| Opus 5 | $0.00014 | $0.00722 |
| Sonnet 5 | $0.00006 | $0.00289 |
| Haiku 4.5 | $0.00003 | $0.00144 |
Grade A, and why
testing scanned grade A with 0 findings 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 2d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Test-Driven Development
Write the test first. Watch it fail. Write minimal code to pass.
The Iron Law
NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST
If you didn't watch the test fail, you don't know if it tests the right thing.
Write code before the test? Delete it. Start over.
When to Use
Always:
- New features
- Bug fixes
- Refactoring
- Behavior changes
Exceptions (ask first):
- Throwaway prototypes
- Generated code
- Configuration files
Thinking "skip TDD just this once"? Stop. That's rationalization.
Red-Green-Refactor
RED - Write Failing Test
Write one minimal test showing what should happen.
// Good: Clear name, tests real behavior, one thing
test('rejects empty email', async () => {
const result = await submitForm({ email: '' });
expect(result.error).toBe('Email required');
});
// Bad: Vague name, tests mock not code
test('form works', async () => {
const mock = jest.fn().mockResolvedValue('success');
await submitForm(mock);
expect(mock).toHaveBeenCalled();
});
Requirements:
- One behavior per test
- Clear descriptive name
- Real code (no mocks unless unavoidable)
Verify RED - Watch It Fail
MANDATORY. Never skip.
npm test path/to/test.test.ts
Confirm:
- Test fails (not errors)
- Failure message is expected
- Fails because feature missing (not typos)
Test passes? You're testing existing behavior. Fix the test.
GREEN - Minimal Code
Write the simplest code to pass the test.
// Good: Just enough to pass
function validateEmail(email: string): string | null {
if (!email?.trim()) return 'Email required';
return null;
}
// Bad: Over-engineered
function validateEmail(
email: string,
options?: {
allowEmpty?: boolean;
customRegex?: RegExp;
onValidate?: (email: string) => void;
}
): ValidationResult {
// YAGNI - don't add features not tested
}
Don't add features, refactor other code, or "improve" beyond the test.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 255 lines · 28 tokens per session scan A 96732e5bb42f
testing is a skill published in the GitHub repository AvinashP/AgentsAtlas (7 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 1,443 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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