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 softspark/ai-toolkit --skill testing-patternsgit clone --depth 1 https://github.com/softspark/ai-toolkitWrote 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/softspark/ai-toolkit/testing-patterns)<a href="https://agentmods.dev/skills/softspark/ai-toolkit/testing-patterns"><img src="https://agentmods.dev/badge/skills/softspark/ai-toolkit/testing-patterns/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/softspark/ai-toolkit/testing-patterns"><img src="https://agentmods.dev/badge/skills/softspark/ai-toolkit/testing-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00052 | $0.01453 |
| Opus 5.5 | $0.00021 | $0.00581 |
| Sonnet 5.5 | $0.00010 | $0.00291 |
| Haiku 4.5 | $0.00005 | $0.00145 |
Grade A, and why
testing-patterns 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 1mo 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Testing Patterns Skill
Test Structure (AAA Pattern)
def test_function_does_expected_thing():
"""Test description explaining what and why."""
# Arrange - Set up test data and preconditions
input_data = {"key": "value"}
expected = "result"
# Act - Execute the code under test
result = function_under_test(input_data)
# Assert - Verify the outcome
assert result == expected
Test Organization
tests/
├── conftest.py # Shared fixtures
├── unit/ # Unit tests (isolated)
│ ├── test_search_core.py
│ └── test_utils.py
├── integration/ # Integration tests
│ └── test_api.py
└── e2e/ # End-to-end tests
└── test_workflow.py
Quality Targets
| Metric | Target |
|---|---|
| Coverage | >70% overall |
| New code | 100% |
| Core modules | >80% |
| No flaky tests | 0 |
Validation contract regressions
Mirrored validators can agree on a generated snapshot while disagreeing on real inputs. Execute the same accepted/rejected fixtures against the real backend validator and the client evaluator. Include N/N+1 boundaries, collection/item limits, omitted/null/empty/default values, nested paths, conditional branches, hydrated updates versus fresh DTOs, Unicode units and previously valid inputs.
Test the actual HTTP path for malformed input and unchanged persisted state after a pre-write refusal. Test zero transport calls for a local refusal, normal transport for a valid payload, and field correction/resubmission. Run deterministic-generation and reviewed-exclusion checks separately from behavioral parity. A schema/rule count is inventory, not assertion coverage.
For operation semantics and runtime mismatches, read
reference/input-validation.md from the installed security-patterns skill.
Resolve the skill through the current client's catalog; directory names may
carry an adapter-specific prefix.
Language-Specific References
| Language | Reference | Key Topics |
|---|---|---|
| Python | reference/python-pytest.md | Fixtures, mocking, parametrize, markers, conftest, running tests |
| TypeScript | reference/typescript-vitest.md | Vitest/Jest, React Testing Library, mocking, running tests |
| PHP | reference/php-phpunit.md | PHPUnit test cases, mocking, running tests |
| Go | reference/go-testing.md | Table-driven tests, testify mocking, running tests |
| Flutter/Dart | reference/flutter-testing.md | Widget tests, unit tests, running tests |
What ships with it
5 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.
- 1mo ago Changed · +19 lines d89d4c5a6ac5
- 1mo ago First seen · 111 lines · 52 tokens per session scan A 838e60336ca9
testing-patterns is a skill published in the GitHub repository softspark/ai-toolkit (180 stars, last pushed 4d ago), licensed Apache-2.0. It adds 52 tokens to every session and 1,453 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
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