Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
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Use when a test is failing and you need to determine root cause: is it flaky, an environment issue, or a real regression? Traces failure from symptom to fix.
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Runbook-style skill for systematic test failure investigation. Given a failing test, determines root cause and recommends action.
/test-failure-investigator [test-name-or-file]
Run the test 3 times and classify:
| Result Pattern | Classification | Action |
|---|---|---|
| Fails consistently | Regression or Environment | Continue to Step 2 |
| Fails intermittently | Flaky | Skip to Step 4 |
| Passes now | Transient | Check CI logs, environment diff |
# Run test 3 times
for i in 1 2 3; do npx jest {{test_file}} 2>&1 | tail -5; echo "--- Run $i ---"; done
# When did it start failing?
git log --oneline -20 -- {{related_source_files}}
# What changed recently?
git diff HEAD~5 -- {{related_source_files}}
# Does it fail in isolation?
npx jest {{test_file}} --testNamePattern="{{test_name}}"
# Does it fail with other tests?
npx jest --runInBand # sequential execution
| Symptom | Likely Cause | Investigation |
|---|---|---|
| Timeout | Network/DB dependency | Check external service availability |
| Assertion mismatch | Logic change | Compare expected vs actual, check git blame |
| Import error | Dependency change | Check package.json changes, run npm ci |
| Permission denied | Environment | Check file permissions, Docker volumes |
| Out of memory | Resource leak | Profile with --detectOpenHandles |
# Run 10 times to confirm flakiness
for i in $(seq 1 10); do npx jest {{test_file}} --forceExit 2>&1 | grep -E 'PASS|FAIL'; done
# Common flaky causes:
# - Shared state between tests (missing cleanup)
# - Time-dependent assertions (use fake timers)
# - Race conditions (missing await)
# - Port conflicts (use random ports)
# - Order dependency (run with --randomize)
## Test Failure Report
- **Test**: {{test_name}}
- **File**: {{test_file}}
- **Classification**: Regression / Flaky / Environment / Transient
- **Root Cause**: {{description}}
- **First Failed**: {{commit_hash}} ({{date}})
- **Fix**: {{recommended_action}}
- **Verified**: [ ] Fix applied and test passes 3x consecutively
After investigation, compose with:
/bug-reporting-excellence — if regression found, file a bug report/regression-testing — if regression, add to regression suite/qe-test-execution — for re-running tests after fix还没有评价。欢迎分享你的使用感受。
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Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
中文简介正在准备中。当前显示原文说明。
WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
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Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
中文简介正在准备中。当前显示原文说明。