review
Review Playwright tests for quality. Use when user says "review tests", "check test quality", "audit tests", "improve tests", "test code review", or "playwright best practices check".
- License 许可
- MIT
- 最近更新
- 2026-09-22
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- ★ 0
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- 0
01 前言 Front Matter
- name
- review
- description
- Review Playwright tests for quality. Use when user says "review tests", "check test quality", "audit tests", "improve tests", "test code review", or "playwright best practices check".
02 资源文件 1
- 参考文档anti-patterns.md4.2 KB
03 SKILL.md 正文
Review Playwright Tests
Systematically review Playwright test files for anti-patterns, missed best practices, and coverage gaps.
Input
$ARGUMENTS can be:
- A file path: review that specific test file
- A directory: review all test files in the directory
- Empty: review all tests in the project's
testDir
Steps
1. Gather Context
- Read
playwright.config.tsfor project settings - List all
*.spec.ts/*.spec.jsfiles in scope - If reviewing a single file, also check related page objects and fixtures
2. Check Each File Against Anti-Patterns
Load anti-patterns.md from this skill directory. Check for all 20 anti-patterns.
Critical (must fix):
waitForTimeout()usage- Non-web-first assertions (
expect(await ...)) - Hardcoded URLs instead of
baseURL - CSS/XPath selectors when role-based exists
- Missing
awaiton Playwright calls - Shared mutable state between tests
- Test execution order dependencies
Warning (should fix):
8. Tests longer than 50 lines (consider splitting)
9. Magic strings without named constants
10. Missing error/edge case tests
11. page.evaluate() for things locators can do
12. Nested test.describe() more than 2 levels deep
13. Generic test names ("should work", "test 1")
Info (consider):
14. No page objects for pages with 5+ locators
15. Inline test data instead of factory/fixture
16. Missing accessibility assertions
17. No visual regression tests for UI-heavy pages
18. Console error assertions not checked
19. Network idle waits instead of specific assertions
20. Missing test.describe() grouping
3. Score Each File
Rate 1-10 based on:
- 9-10: Production-ready, follows all golden rules
- 7-8: Good, minor improvements possible
- 5-6: Functional but has anti-patterns
- 3-4: Significant issues, likely flaky
- 1-2: Needs rewrite
4. Generate Review Report
For each file:
## <filename> — Score: X/10
### Critical
- Line 15: `waitForTimeout(2000)` → use `expect(locator).toBeVisible()`
- Line 28: CSS selector `.btn-submit` → `getByRole('button', { name: "submit" })`
### Warning
- Line 42: Test name "test login" → "should redirect to dashboard after login"
### Suggestions
- Consider adding error case: what happens with invalid credentials?
5. For Project-Wide Review
If reviewing an entire test suite:
- Spawn sub-agents per file for parallel review (up to 5 concurrent)
- Or use
/batchfor very large suites - Aggregate results into a summary table
6. Offer Fixes
For each critical issue, provide the corrected code. Ask user: "Apply these fixes? [Yes/No]"
If yes, apply all fixes using Edit tool.
Output
- File-by-file review with scores
- Summary: total files, average score, critical issue count
- Actionable fix list
- Coverage gaps identified (pages/features with no tests)
04 同仓库更多 Skills
syllabus
Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Triggers whenever a user uploads a syllabus, course outline, or curriculum document and wants supplementary readings. Also triggers on: 'syllabus reading list', 'find papers for my course', 'create a reading list from this syllabus', 'recent research for my class', 'supplementary readings', 'find journal articles for these topics', 'what recent papers cover this material', 'any new research on these course topics', 'update my syllabus with recent papers'. Even casual mentions when a syllabus is attached should trigger this skill.
research
Default entry point for any research request — a hybrid router that classifies the question deterministically and either delegates to a specialist research skill (pulse for trends/sentiment, grants for NIH funding, litreview for academic literature, syllabus for course reading, patent for prior-art + IP landscape, dossier for entity research) or runs its own plan-decompose-multi-source-search-synthesize-cite fallback workflow when no specialist matches. Always surfaces the routing decision so users can override. Triggers — "research [topic]", "look into [topic]", "what do we know about [topic]", "investigate [topic]", "find me information on [topic]", "do some research on [topic]", "I need to understand [topic]", or any research request that doesn't obviously match a more-specific specialist skill. Output is a markdown briefing (default) or .docx document (on request) with full citations and an audit log.
pulse
Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Triggers: 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]', or any variation requesting multi-source recency intelligence on a topic. Also use for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.
patent
Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search / freedom-to-operate / competitive landscape / acquisition diligence / litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Triggers: 'prior art search for [invention]', 'patent search on [topic]', 'freedom to operate analysis', 'FTO for [product]', 'patent landscape for [field]', 'is [invention] novel', 'patents on [topic]', 'competitive patent analysis', 'prior art for litigation', 'patent diligence on [company]'. Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.
notebooklm
Browser automation skill for controlling Google's NotebookLM. Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio Overview, infographics, slide decks, study guides, briefing docs, mind maps, timelines, FAQs), and creating new notebooks. Triggers on any phrase involving NotebookLM — 'open NotebookLM', 'check my [name] notebook', 'pull info from NotebookLM', 'ask my notebook about X', 'add [source] to NotebookLM', 'create an infographic in NotebookLM', 'use NotebookLM Studio', 'generate a slide deck from my notebook', or any variation where the goal involves NotebookLM. Requires browser automation environment — fails gracefully when unavailable.
litreview
Academic literature orientation skill that searches papers via Consensus, builds a strategic search plan using PICO (default) or SPIDER / Decomposition / hybrid as fallbacks, and synthesizes findings into a professionally formatted Word document (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5/10/20 queries) controls coverage vs. speed. Output is a 'launching pad' — not a finished review, but an orientation guide that lets a researcher dive in confidently. Triggers: 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'. Do NOT trigger for single one-off paper searches where the user just wants a quick list — that's a plain Consensus search.