AI-powered adeno-associated virus (AAV) vector design for gene therapy including capsid engineering, promoter selection, and tropism optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Replace arbitrary timeouts with condition polling for reliable async tests
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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):
This skill is written to stay usable across GitHub Copilot, Claude Code, and Codex.
$CODEX_HOME/skills/condition-based-waiting and restart Codex after major changes.Preferred MCP Server: None required
condition-based-waiting outside its documented task boundary.Before claiming the condition-based-waiting workflow succeeded:
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
AI-powered adeno-associated virus (AAV) vector design for gene therapy including capsid engineering, promoter selection, and tropism optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Improve the clarity and voice of AI-assisted academic writing (papers, theses, rebuttals) and
日本語の概要は準備中です。原文の説明を表示しています。
12-agent academic paper writing pipeline. 11 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure/rebuttal-audit). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, audit my rebuttal, check my response draft, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見, 評估回覆, 논문 작성, 초록 작성, 논문 수정, 논문 계획을 도와줘, 심사 의견 반영, 답변서 점검, AI 사용 고지.
日本語の概要は準備中です。原文の説明を表示しています。
Systematic writing framework for philosophy and interdisciplinary academic papers from optimized outline to submission-ready manuscript. Use when users want to: (1) write a paper from a detailed outline, (2) ensure quality control during writing, (3) maintain consistency across chapters, (4) prepare a submission-ready manuscript, or (5) systematically execute a planned paper. Triggered by phrases like 'write the paper from this outline,' 'compose the full manuscript,' 'execute the outline,' or when users have completed strategic planning (academic-paper-strategist skill) and are ready to write. Takes optimized outline as input; outputs complete manuscript with iterative quality checks.
日本語の概要は準備中です。原文の説明を表示しています。
Multi-perspective academic paper review with dynamic reviewer personas. Runs a 5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate) with field-specific expertise; role separation is not a claim of independent error processes. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy, 審查論文, 論文審查, 模擬審查, 同儕審查, 幫我審這篇, 以審查人角度評估, 審查者校準, 논문 심사, 동료 심사, 모의 심사, 심사자 관점에서 평가, 심사자 보정.
日本語の概要は準備中です。原文の説明を表示しています。
Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints.
日本語の概要は準備中です。原文の説明を表示しています。