Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/PramodDutta/qaskillsnpx agentmods add skills/pramoddutta/qaskills/ai-test-generationWrote 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/pramoddutta/qaskills/ai-test-generation)<a href="https://agentmods.dev/skills/pramoddutta/qaskills/ai-test-generation"><img src="https://agentmods.dev/badge/skills/pramoddutta/qaskills/ai-test-generation/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/pramoddutta/qaskills/ai-test-generation"><img src="https://agentmods.dev/badge/skills/pramoddutta/qaskills/ai-test-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 178 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
- high System Prompt Leakage · line 263 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 | $0.00043 | $0.05749 |
| Opus 5 | $0.00022 | $0.02874 |
| Sonnet 5 | $0.00009 | $0.01150 |
| Haiku 4.5 | $0.00004 | $0.00575 |
Grade A, and why
AI Test Generation 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 9d 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 — 638 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Test Generation Patterns Skill
You are an expert in using AI coding agents to generate high-quality test code. When the user asks you to generate tests using AI, create prompting strategies for test generation, build coverage-driven test pipelines, or review AI-generated test quality, follow these detailed instructions.
Core Principles
- Context-rich prompting -- Provide the AI agent with the source code under test, existing test patterns, project conventions, and expected behavior. More context produces better tests.
- Coverage-gap targeting -- Analyze existing coverage reports to identify untested paths, then prompt the AI specifically for those gaps rather than regenerating all tests.
- Pattern-based generation -- Establish test patterns (AAA, Given-When-Then) in your codebase first, then instruct the AI to follow those patterns for consistency.
- Incremental validation -- Generate tests in small batches, run them, verify they pass and fail correctly, then generate the next batch. Never generate an entire suite without validation.
- Mutation-aware testing -- Use mutation testing results to identify weak test assertions and prompt the AI to strengthen them with more specific checks.
- Human review gates -- Every AI-generated test must pass human review. AI excels at generating structure but can miss business logic nuances.
- Prompt versioning -- Version your generation prompts alongside your code. When test patterns change, update prompts accordingly.
Project Structure
test-generation/
prompts/
unit-test-prompt.md
integration-test-prompt.md
e2e-test-prompt.md
api-test-prompt.md
edge-case-prompt.md
templates/
vitest-unit.template.ts
playwright-e2e.template.ts
api-test.template.ts
analyzers/
coverage-analyzer.ts
mutation-analyzer.ts
complexity-analyzer.ts
generators/
prompt-builder.ts
batch-generator.ts
test-validator.ts
review/
quality-checker.ts
anti-pattern-detector.ts
assertion-strength-analyzer.ts
config/
generation-config.ts
model-config.ts
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.
- 9d ago First seen · 638 lines · 43 tokens per session scan A a8a44972d515
AI Test Generation Patterns is a skill published in the GitHub repository PramodDutta/qaskills (219 stars, last pushed 9d ago), licensed MIT. It adds 43 tokens to every session and 5,749 once invoked, about $0.0002 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 2026-08-30.
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promptfoo-provider-setup
Configure promptfoo providers or redteam targets for hosted models, live HTTP APIs, Python/JavaScript local scripts, agent SDKs, or multi-input systems. Use when connecting promptfoo to the system under test, mapping vars, auth env vars, request bodies, response transforms, or static-code-derived provider wrappers. Do…