alirezarezvani/report
engineering-team/playwright-pro/skills/report/SKILL.md
Generate test report. Use when user says "test report", "results summary", "test status", "show results", "test dashboard", or "how did tests go".
$ install --global
skillsauthnpx skillsauth add alirezarezvani/claude-skills reportInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 4, 2026, 5:51 PM4.2s1 file scanned
SKILL.md
- name:
- report
- description:
- >-
Smart Test Reporting
Generate test reports that plug into the user's existing workflow. Zero new tools.
Steps
1. Run Tests (If Not Already Run)
Check if recent test results exist:
ls -la test-results/ playwright-report/ 2>/dev/null
If no recent results, run tests:
npx playwright test --reporter=json,html,list 2>&1 | tee test-output.log
2. Parse Results
Read the JSON report:
npx playwright test --reporter=json 2> /dev/null
Extract:
- Total tests, passed, failed, skipped, flaky
- Duration per test and total
- Failed test names with error messages
- Flaky tests (passed on retry)
3. Detect Report Destination
Check what's configured and route automatically:
| Check | If found | Action |
|---|---|---|
| TESTRAIL_URL env var | TestRail configured | Push results via /pw:testrail push |
| SLACK_WEBHOOK_URL env var | Slack configured | Post summary to Slack |
| .github/workflows/ | GitHub Actions | Results go to PR comment via artifacts |
| playwright-report/ | HTML reporter | Open or serve the report |
| None of the above | Default | Generate markdown report |
4. Generate Report
Markdown Report (Always Generated)
# Test Results — {{date}}
## Summary
- ✅ Passed: {{passed}}
- ❌ Failed: {{failed}}
- ⏭️ Skipped: {{skipped}}
- 🔄 Flaky: {{flaky}}
- ⏱️ Duration: {{duration}}
## Failed Tests
| Test | Error | File |
|---|---|---|
| {{name}} | {{error}} | {{file}}:{{line}} |
## Flaky Tests
| Test | Retries | File |
|---|---|---|
| {{name}} | {{retries}} | {{file}} |
## By Project
| Browser | Passed | Failed | Duration |
|---|---|---|---|
| Chromium | X | Y | Zs |
| Firefox | X | Y | Zs |
| WebKit | X | Y | Zs |
Save to test-reports/{{date}}-report.md.
Slack Summary (If Webhook Configured)
curl -X POST "$SLACK_WEBHOOK_URL" \
-H 'Content-Type: application/json' \
-d '{
"text": "🧪 Test Results: ✅ {{passed}} | ❌ {{failed}} | ⏱️ {{duration}}\n{{failed_details}}"
}'
TestRail Push (If Configured)
Invoke /pw:testrail push with the JSON results.
HTML Report
npx playwright show-report
Or if in CI:
echo "HTML report available at: playwright-report/index.html"
5. Trend Analysis (If Historical Data Exists)
If previous reports exist in test-reports/:
- Compare pass rate over time
- Identify tests that became flaky recently
- Highlight new failures vs. recurring failures
Output
- Summary with pass/fail/skip/flaky counts
- Failed test details with error messages
- Report destination confirmation
- Trend comparison (if historical data available)
- Next action recommendation (fix failures or celebrate green)
Related Skills
alirezarezvani/code-reviewer
tools
VerifiedTrustedCommunity
Code review automation for TypeScript, JavaScript, Python, Go, Swift, Kotlin, C#, .NET, Java, C, C++, Rust, Ruby, PHP, and Dart/Flutter. Analyzes PRs for complexity and risk, checks code quality for SOLID violations and code smells, generates review reports. Use when reviewing pull requests, analyzing code quality, identifying issues, generating review checklists.
16,546SKILL.mdUpdated May 10, 2026
alirezarezvani/research-ops-skills
tools
VerifiedTrustedCommunity
Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market sizing/surveys, or product/user research. Triggers on "design this clinical study", "what sample size", "R&D budget", "burn rate", "capitalize or expense", "TAM SAM SOM", "market sizing", "survey design", "segment the market", "plan user interviews", "usability test", "synthesize research insights". Forks context to route to one of four Research-Operations sub-skills (clinical-research, research-finance, market-research, product-research) and returns a digest. Distinct from ra-qm-team (regulatory submission), finance (corporate close/valuation), research/grants (funding discovery), product-team (persona/journey/live experiments), and marketing-skill (campaign analytics).
16,359SKILL.mdUpdated May 28, 2026
alirezarezvani/research-finance
development
VerifiedTrustedCommunity
Use when managing the money for an internal R&D program or portfolio — building a multi-period program budget with the F&A (indirect) split, tracking burn rate and runway against value-inflection milestones, or routing R&D cost items to a capitalize-vs-expense determination. Every budget output surfaces its assumptions block; capitalize-vs-expense is decision-support only and routes to a named finance owner — it never books an entry or decides accounting treatment. Distinct from finance/financial-analysis (corporate DCF, close, valuation) and research/grants (funding discovery — this manages money already won).
16,359SKILL.mdUpdated May 28, 2026
alirezarezvani/product-research
development
VerifiedTrustedCommunity
Use when planning and synthesizing product/user research as a method-and-repository discipline — selecting the right method for the goal (generative interviews vs usability test vs concept test vs validation), computing method-based saturation/sample size with an explicit confidence level, or synthesizing coded observations into insights while flagging single-source anecdotes. Never fabricates user insight; an insight requires recurrence across independent participants. Distinct from product-team/ux-researcher-designer (persona/journey artifacts), product-discovery (discovery-sprint planning), and experiment-designer (live A/B) — this is the research-ops method + insight-repository layer.
16,359SKILL.mdUpdated May 28, 2026