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Teach agents to manage Jira test cases and executions with Xray and Zephyr, including issue modeling, JQL, and CI result publishing through REST APIs.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/PramodDutta/qaskills --skill acceptance-reportingコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
Use when publishing SEO blog articles to qaskills.sh, e.g. "publish today's articles", "daily SEO batch", "write 10 articles from keyword research", "add a blog post", or any request that creates files under packages/web/src/app/blog/posts.
Generate test data from the schemas you already have. Read OpenAPI, JSON Schema, SQL DDL, or TypeScript models and produce deterministic factories, boundary and negative cases, relational datasets with valid foreign keys, cleanup scripts, and PII-safe synthetic data. Production records never leave the machine.
Analyze a git diff, map affected risks, select the tests that matter, detect coverage gaps on changed lines, run configurable quality gates, and produce a go/no-go release report with cited evidence. Recommends only; never merges or deploys.
SOC 職業分類に基づく
SKILL.md を表示中
| name | Xray Zephyr Jira Testing |
| description | Teach agents to manage Jira test cases and executions with Xray and Zephyr, including issue modeling, JQL, and CI result publishing through REST APIs. |
| version | 1.0.0 |
| author | thetestingacademy |
| license | MIT |
| tags | ["jira","xray","zephyr","test-management","reporting","rest-api"] |
| testingTypes | ["strategy","reporting","acceptance"] |
| frameworks | [] |
| languages | ["python","typescript"] |
| domains | ["web","api"] |
| agents | ["claude-code","cursor","github-copilot","windsurf","codex","aider","continue","cline","zed","bolt","gemini-cli","amp"] |
You are a test management engineer who organizes Jira-based test cases, links them to requirements, and publishes automated execution results to Xray or Zephyr with traceable REST integrations.
Create API credentials and store them in CI secrets.
export JIRA_BASE_URL='https://example.atlassian.net'
export JIRA_EMAIL='qa@example.com'
export JIRA_API_TOKEN='replace-me'
export XRAY_CLIENT_ID='replace-me'
export XRAY_CLIENT_SECRET='replace-me'
Install local helper dependencies.
python -m venv .venv
. .venv/bin/activate
pip install requests pydantic python-dotenv
npm install --save-dev @playwright/test
Keep mapping files in source control.
test-management/
mappings/
playwright-to-jira.json
requirements-to-tests.csv
queries/
release-readiness.jql
scripts/
publish-xray-results.py
publish-zephyr-results.ts
reports/
.gitkeep
Use this minimum model.
| Entity |
|---|
| Xray Name |
|---|
| Zephyr Name |
|---|
| Purpose |
|---|
| Requirement | Story or Task | Story or Task | Business behavior |
| Test case | Test | Test Case | Reusable verification |
| Test execution | Test Execution | Test Cycle | Run instance |
| Defect | Bug | Bug | Failed behavior |
| Release | Fix Version | Version | Reporting boundary |
| Automation id | Custom field or label | Custom field or label | CI mapping |
Use JQL to find coverage and execution gaps.
project = QA AND issuetype = Test AND labels in (checkout) ORDER BY updated DESC
project = QA AND issuetype = Bug AND priority in (Highest, High) AND statusCategory != Done
project = QA AND fixVersion = "2026.07" AND issuetype = Test AND status != Deprecated
project = QA AND labels = automated AND "Automation Status" = Ready
Publish JUnit XML or structured results to Xray after CI.
# test-management/scripts/publish_xray_results.py
import os
import requests
base_url = os.environ["JIRA_BASE_URL"]
client_id = os.environ["XRAY_CLIENT_ID"]
client_secret = os.environ["XRAY_CLIENT_SECRET"]
junit_path = os.environ.get("JUNIT_PATH", "test-results/junit.xml")
token_response = requests.post(
"https://xray.cloud.getxray.app/api/v2/authenticate",
json={"client_id": client_id, "client_secret": client_secret},
timeout=30,
)
token_response.raise_for_status()
token = token_response.json()
with open(junit_path, "rb") as report:
response = requests.post(
"https://xray.cloud.getxray.app/api/v2/import/execution/junit",
headers={"Authorization": f"Bearer {token}"},
files={"file": report},
timeout=60,
)
response.raise_for_status()
print(response.json())
Use a typed script for Zephyr Scale or Zephyr Squad integrations.
// test-management/scripts/publish-zephyr-results.ts
type TestResult = {
testCaseKey: string;
status: 'Pass' | 'Fail' | 'Blocked' | 'Not Executed';
comment?: string;
};
async function publishResult(result: TestResult): Promise<void> {
const response = await fetch(`${process.env.JIRA_BASE_URL}/rest/atm/1.0/testrun`, {
method: 'POST',
headers: {
Authorization: `Bearer ${process.env.ZEPHYR_TOKEN}`,
'Content-Type': 'application/json',
},
body: JSON.stringify({
testCaseKey: result.testCaseKey,
status: result.status,
comment: result.comment,
}),
});
if (!response.ok) {
throw new Error(`Zephyr publish failed: ${response.status}`);
}
}
await publishResult({ testCaseKey: 'QA-T123', status: 'Pass', comment: 'CI run passed' });
Run tests, upload JUnit, then publish to Jira.
name: acceptance-reporting
on:
workflow_dispatch:
push:
branches: [main]
jobs:
publish:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: 20
- run: npm ci
- run: npx playwright test --reporter=junit
- run: python test-management/scripts/publish_xray_results.py
env:
JIRA_BASE_URL: ${{ secrets.JIRA_BASE_URL }}
XRAY_CLIENT_ID: ${{ secrets.XRAY_CLIENT_ID }}
XRAY_CLIENT_SECRET: ${{ secrets.XRAY_CLIENT_SECRET }}
JUNIT_PATH: test-results/junit.xml