qe

qe is a skill for Claude Code from quay/ai-helpers. It costs 46 tokens per session (3,565 once invoked), scanned A, original, MIT.

A quality-engineering skill that creates and runs a manual test plan for a JIRA ticket. It checks the requested behavior, normal user workflows, edge cases, and effects on existing features.

In plain words
What is it for?
It is for testing container-registry features and fixes from JIRA, including regression checks and scenario-by-scenario verification.
Why use it?
It turns acceptance criteria and reproduction steps into explicit checks, reducing the chance that a feature is tested only along its happy path.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool.

Part of the dev plugin — 16 skills, 1 command shipped together

Good fit It is for testing container-registry features and fixes from JIRA, including regression checks and scenario-by-scenario verification.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/quay/ai-helpers/qe
Install

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.

Any agent
npx skills add quay/ai-helpers --skill qe
Clone the repo
git clone --depth 1 https://github.com/quay/ai-helpers

Made for: Claude Code.

Or install dev, the plugin that ships this one along with the rest of its 16 skills, 1 command.

Wrote 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.

agentmods badge for qe

README.md
[![agentmods](https://agentmods.dev/badge/skills/quay/ai-helpers/qe.svg)](https://agentmods.dev/skills/quay/ai-helpers/qe)
Your own site
<a href="https://agentmods.dev/skills/quay/ai-helpers/qe"><img src="https://agentmods.dev/badge/skills/quay/ai-helpers/qe.svg" alt="Measured on agentmods" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,565 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00046 $0.03565
Opus 5 $0.00023 $0.01783
Sonnet 5 $0.00009 $0.00713
Haiku 4.5 $0.00005 $0.00357

Measured 2d ago against content hash cb5a44a7a1e7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

qe 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.

plugins/dev/skills/qe/SKILL.md · 270 lines

How it starts

The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Create a test plan for a PROJQUAY JIRA ticket, validate it with the user, then execute each scenario as manual verification.

Argument: $ARGUMENTS (JIRA ticket key, e.g., PROJQUAY-1234. Optionally followed by a PR URL or number.)

You are a quality engineer with 10 years of experience testing container registry software. You think like a real user — not a developer who wrote the code. You look for the gaps between what was specified, what was built, and what users will actually do.

You MUST complete each step in order. Do not skip steps or proceed without user confirmation where indicated.

Step 1: Gather JIRA Context

Run these commands to read the full ticket:

acli jira workitem view $ARGUMENTS --fields '*all' --json
acli jira workitem comment list --key $ARGUMENTS

Extract and organize:

  • Summary and Description — what the feature or fix does
  • Acceptance Criteria — every AC becomes a mandatory test scenario; if none exist, stop and ask the user to provide them
  • Steps to Reproduce (for bugs) — these become your baseline regression test
  • Expected Behavior — the definition of "pass" for each scenario
  • Priority / Fix Versions — release context affects test urgency and scope
  • Labels / Components — affected Quay subsystems (tells you where to look for conflicts)
  • Comments — engineer decisions, edge cases mentioned, workarounds reported by users
  • Linked Issues — related bugs, parent epics, or features that share the same code paths

Step 2: Find the Merged PR(s)

If a PR URL or number was provided in the arguments, use it. Otherwise, search for the PR:

# Search by JIRA key in PR titles and bodies across both repos
gh pr list --repo quay/quay --state merged --search "<JIRA_KEY>" --limit 10 --json number,title,url,mergedAt
gh pr list --repo quay/quay-operator --state merged --search "<JIRA_KEY>" --limit 10 --json number,title,url,mergedAt

If no PR is found, ask the user: "I couldn't find a merged PR for this ticket. Please provide the PR URL(s) so I can review what was implemented."

Read the full file on GitHub · 270 lines

Changes

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.

  1. 2d ago First seen · 270 lines · 46 tokens per session scan A cb5a44a7a1e7

Subscribe to this mod's changes

qe is a skill published in the GitHub repository quay/ai-helpers (3 stars, last pushed 19d ago), licensed MIT. It adds 46 tokens to every session and 3,565 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 2026-09-04.

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