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/keithhegit/ultra-orchestration/qa-verifynpx skills add keithhegit/ultra-orchestration --skill qa-verifygit clone --depth 1 https://github.com/keithhegit/ultra-orchestrationWrote 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/keithhegit/ultra-orchestration/qa-verify)<a href="https://agentmods.dev/skills/keithhegit/ultra-orchestration/qa-verify"><img src="https://agentmods.dev/badge/skills/keithhegit/ultra-orchestration/qa-verify.svg" alt="Measured on agentmods" 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 | $0.00038 | $0.00210 |
| Opus 5 | $0.00019 | $0.00105 |
| Sonnet 5 | $0.00008 | $0.00042 |
| Haiku 4.5 | $0.00004 | $0.00021 |
Grade A, and why
qa-verify 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 4d 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.
What it actually says
QA Verify
Validate behavior, not just code shape.
Treat QA as two-mode verification:
- Static baseline: reason over code, diffs, existing tests, and available evidence
- Dynamic verification: run tests or commands when the host environment allows it
Do not assume browser automation exists unless the environment explicitly provides it.
Check
- Happy path
- Error path
- Regression risk
- User-visible behavior
- Follow-up tests that should exist even if they are not added now
Failure handling
- If behavior is wrong but the plan is still valid, send the work back to
Execute. - If QA reveals a deeper architecture or requirement flaw, send the work back to
Plan.
Output
Return:
- scenarios exercised
- evidence collected
- pass or fail status
- residual risks
What ships with it
1 file 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.
- 4d ago First seen · 38 lines · 38 tokens per session scan A 29561942e4f7
qa-verify is a skill published in the GitHub repository keithhegit/ultra-orchestration (6 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 38 tokens to every session and 210 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 2026-08-31.
Other skills, from other repositories
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gsd-audit-uat
Cross-phase audit of all outstanding UAT and verification items.
allium
Give your AI agents something more useful than a prompt. Velocity through clarity.
test
Proves that a code change meets its acceptance criteria. Uses focused automated checks and a real browser for browser-facing work. Use to test or verify a diff, branch, PR, URL, or user flow.
load-test-ops
Trigger, monitor, update, profile, and stop Camunda load tests using gh CLI and kubectl directly — no MCP server required.