Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
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Use when tests have race conditions, timing dependencies, or inconsistent pass/fail behavior - replaces arbitrary timeouts with condition polling to wait for actual state changes, eliminating flaky tests from timing guesses
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Flaky tests often guess at timing with arbitrary delays. This creates race conditions where tests pass on fast machines but fail under load or in CI.
Core principle: Wait for the actual condition you care about, not a guess about how long it takes.
digraph when_to_use {
"Test uses setTimeout/sleep?" [shape=diamond];
"Testing timing behavior?" [shape=diamond];
"Document WHY timeout needed" [shape=box];
"Use condition-based waiting" [shape=box];
"Test uses setTimeout/sleep?" -> "Testing timing behavior?" [label="yes"];
"Testing timing behavior?" -> "Document WHY timeout needed" [label="yes"];
"Testing timing behavior?" -> "Use condition-based waiting" [label="no"];
}
Use when:
setTimeout, sleep, time.sleep())Don't use when:
// ❌ BEFORE: Guessing at timing
await new Promise(r => setTimeout(r, 50));
const result = getResult();
expect(result).toBeDefined();
// ✅ AFTER: Waiting for condition
await waitFor(() => getResult() !== undefined);
const result = getResult();
expect(result).toBeDefined();
| Scenario | Pattern |
|---|---|
| Wait for event | waitFor(() => events.find(e => e.type === 'DONE')) |
| Wait for state | waitFor(() => machine.state === 'ready') |
| Wait for count | waitFor(() => items.length >= 5) |
| Wait for file | waitFor(() => fs.existsSync(path)) |
| Complex condition | waitFor(() => obj.ready && obj.value > 10) |
Generic polling function:
async function waitFor<T>(
condition: () => T | undefined | null | false,
description: string,
timeoutMs = 5000
): Promise<T> {
const startTime = Date.now();
while (true) {
const result = condition();
if (result) return result;
if (Date.now() - startTime > timeoutMs) {
throw new Error(`Timeout waiting for ${description} after ${timeoutMs}ms`);
}
await new Promise(r => setTimeout(r, 10)); // Poll every 10ms
}
}
See @example.ts for complete implementation with domain-specific helpers (waitForEvent, waitForEventCount, waitForEventMatch) from actual debugging session.
❌ Polling too fast: setTimeout(check, 1) - wastes CPU
✅ Fix: Poll every 10ms
❌ No timeout: Loop forever if condition never met ✅ Fix: Always include timeout with clear error
❌ Stale data: Cache state before loop ✅ Fix: Call getter inside loop for fresh data
// Tool ticks every 100ms - need 2 ticks to verify partial output
await waitForEvent(manager, 'TOOL_STARTED'); // First: wait for condition
await new Promise(r => setTimeout(r, 200)); // Then: wait for timed behavior
// 200ms = 2 ticks at 100ms intervals - documented and justified
Requirements:
From debugging session (2025-10-03):
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Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
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Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
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This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
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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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