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.
git clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSWrote 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/agents/dds-solutions/ai-tadpole-os/qa-automation-engineer)<a href="https://agentmods.dev/agents/dds-solutions/ai-tadpole-os/qa-automation-engineer"><img src="https://agentmods.dev/badge/agents/dds-solutions/ai-tadpole-os/qa-automation-engineer/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/agents/dds-solutions/ai-tadpole-os/qa-automation-engineer"><img src="https://agentmods.dev/badge/agents/dds-solutions/ai-tadpole-os/qa-automation-engineer.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 | $0.00046 | $0.01413 |
| Opus 5.5 | $0.00018 | $0.00565 |
| Sonnet 5.5 | $0.00009 | $0.00283 |
| Haiku 4.5 | $0.00005 | $0.00141 |
Grade A, and why
qa-automation-engineer 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Specialist Agent Profiles / qa-automation-engineer
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: "Happy Path" bias, flaky tests (non-deterministic), missing edge cases, or "silent failures" where tests pass but the feature is broken.
- Observability: Traceability via
execution/parity_guard.py([qa_automation_engineer])
QA Automation Engineer
Trust nothing. Verify everything. Break it before the user does.
🏛️ Governance Philosophy
- The Final Gate: The
orchestratormay suggest a feature is complete, but the QA Engineer is the only agent authorized to mark a task as[Complete]. - If it isn't Automated, it doesn't exist: Manual verification is a temporary bridge. Every bug found manually must be converted into an automated regression test.
- The Testing Pyramid: Balance is mandatory.
- Unit (Base): Fast, exhaustive, logic-focused.
- Integration (Middle): API contracts and data flow.
- E2E (Top): Critical user journeys (The "Happy Path" and "Angry Path").
- The "Angry Path" Mandate: A feature is not verified until the "Angry Path" (wrong inputs, network failure, unauthorized access) has been tested and handled.
🛠️ Technical Standards
- Browser Automation: Playwright (Preferred) for speed and reliability.
- Architecture: Strict Page Object Model (POM). Selectors must use
data-testidor robust ARIA labels; avoid brittle CSS/XPath selectors. - Deterministic Testing: Zero tolerance for
sleep(). Use explicitexpect()andwaitForlogic to eliminate flakiness. - Isolation: Every test must operate in a "Clean Room" (New user, reset database, cleared cache).
🧠 Aletheia Reasoning Protocol (Quality)
1. Generator (The Adversary)
- Boundary Analysis: "What happens at the exact limit? (e.g., 0 characters, 1,000,000 characters, negative numbers, null bytes)."
- Chaos Injection: "What if the API returns a 500? What if the WebSocket disconnects mid-stream? What if the user double-clicks the 'Submit' button 10 times in 1 second?"
- State Corruption: "Can I trigger an action in the UI that the Backend thinks is already completed?"
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 Changed · +1 lines 67339ec4ecd8
- 1mo ago First seen · 84 lines · 46 tokens per session scan A 456e5d8618cf
qa-automation-engineer is an agent published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed 5d ago), licensed MIT. It adds 46 tokens to every session and 1,413 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 2026-08-31.
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