「iab」の検索結果

Browser automation powers web testing, scraping, and AI agent interactions. The difference between a flaky script and a reliable system comes down to understanding selectors, waiting strategies, and anti-detection patterns. This skill covers Playwright (recommended) and Puppeteer, with patterns for testing, scraping, and agentic browser control. Key insight: Playwright won the framework war. Unless you need Puppeteer's stealth ecosystem or are Chrome-only, Playwright is the better choice in 2025. Critical distinction: Testing automation (predictable apps you control) vs scraping/agent automation (unpredictable sites that fight back). Different problems, different solutions. Use when "playwright, puppeteer, browser automation, headless, web scraping, e2e test, end-to-end, selenium, chromium, browser test, page.click, locator, playwright, puppeteer, browser, automation, testing, scraping, headless, e2e, selenium, web-testing" mentioned.

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。

BullMQ expert for Redis-backed job queues, background processing, and reliable async execution in Node.js/TypeScript applications. Use when "bullmq, bull queue, redis queue, background job, job queue, delayed job, repeatable job, worker process, job scheduling, async processing, bullmq, bull, redis, queue, background-jobs, job-processing, async, workers, scheduling, delayed-jobs" mentioned.

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。

World-class backend engineering - distributed systems, database architecture, API design, and the battle scars from scaling systems that handle millions of requestsUse when "backend, api, database, postgres, mysql, mongodb, redis, graphql, rest, authentication, authorization, caching, queue, background job, webhook, migration, transaction, n+1, rate limit, server, node.js, python, go, backend, api, database, architecture, performance, reliability, security" mentioned.

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。

CI/CD is the backbone of modern software delivery. Continuous Integration catches bugs early. Continuous Deployment gets features to users fast. But poorly designed pipelines can be slow, flaky, and a source of constant frustration. This skill covers GitHub Actions (the most popular), GitLab CI, and general pipeline design principles. The focus is on pipelines that are fast, reliable, and maintainable. 2025 reality: Your pipeline is infrastructure code. It deserves the same care as your application. A flaky test in CI is worse than no test - it teaches developers to ignore failures. Use when "github actions, gitlab ci, ci cd, pipeline, workflow, deploy automation, continuous integration, continuous deployment, build pipeline, yaml workflow, ci-cd, github-actions, gitlab-ci, devops, automation, deployment, pipelines" mentioned.

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。

Family-G proof & derivation integrity forensics: does a THIRD PARTY's written proof/derivation actually establish its theorem, or does it skip an obligation, assume its own conclusion, take an invalid step, drift a symbol's meaning, or smuggle an unstated assumption? Decides from the WRITTEN proof/derivation — verdict-bearing at L1 (the LaTeX source; PDF-extracted math is unreliable, so an L0 PDF-only run surfaces info only) — never asserts 'fabricated', only that the step shown does not hold. A fresh cross-model reviewer reads the theorem/proof + an extraction-only obligation scaffold and proposes per-obligation findings, each span-anchored to the evidence ledger (claims.json); reviewer≠adjudicator. Emits proof-derivation-forensics.findings.json; NEVER computes the verdict. dimension=proof, can be critical. Triggers: "proof forensics", "check this proof", "derivation integrity", "audit the math", "证明审计", "推导有没有漏洞".

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。

Analytics Tracking & Measurement Strategy workflow skill. Use this skill when the user needs Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Analytics Tracking & Measurement Strategy workflow skill. Use this skill when the user needs Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Analytics Tracking & Measurement Strategy workflow skill. Use this skill when the user needs Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Analytics Tracking & Measurement Strategy workflow skill. Use this skill when the user needs Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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-Agent Optimization Toolkit workflow skill. Use this skill when the user needs Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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-Agent Optimization Toolkit workflow skill. Use this skill when the user needs Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Design safe queue consumers and retries. Use when a mid-level developer needs reliable background processing.

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。

Review a system architecture for scalability, reliability, and maintainability. Use when a senior developer needs to critique a design.

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。

Distill Opus-level reasoning into optimized instructions for Haiku 5.5 (and Sonnet). Generates explicit, procedural prompts with n-shot examples that maximize smaller model performance on a given task. Use when user says "down-skill", "distill for Haiku", "optimize for Haiku", "make this work on Haiku", "generate Haiku instructions", or needs to delegate a task to a smaller model with high reliability.

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。

Universal environment variable loader for AI agent environments. Loads secrets and config from Claude.ai, Claude Code, OpenAI Codex, Jules, and standard .env files.

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。

Use when operating peky from the CLI or TUI, especially for AI agents who need reliable, low-error procedures. Covers how to target sessions/panes correctly, use scopes, avoid confirmation prompts, and keep CLI/TUI/daemon in sync.

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。

Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

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。

Beginner-first SEO coaching for people who want to learn by doing one safe, verifiable step at a time. Use for SEO 陪跑、學 SEO、逐步檢查網站、看懂 Search Console／GA4、零付費工具的手動無痕 SERP、關鍵字與搜尋意圖、 內容差距、基礎網站架構、content brief、四篇 SEO 寫作實作、流量或排名問題教學， 以及 robots.txt、sitemap、title、canonical、Core Web Vitals 等概念與操作問題。 Do not use for a one-shot full-site audit report or health score, ghostwritten content delivery, PBN/site building, or paid-ad-only advice.

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。

Design surveys that collect reliable, unbiased quantitative data to validate hypotheses and measure user attitudes at scale.

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。

Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.

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。

Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

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。

Applies the behavioral genetics and twin-study methodologies of Dorret I. Boomsma (behavior geneticist, Vrije Universiteit Amsterdam). Use this skill when reasoning about heritability, genetic epidemiology, nature vs. nurture debates, psychiatric genetics, or longitudinal phenotyping. Trigger this whenever the user asks about the genetic basis of intelligence, lifestyle factors, educational attainment, or psychopathology, or when designing epidemiological studies. It helps deconfound environmental and genetic variables using extended family designs and discordant twin models.

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。

Suede-owned experimentation discipline for hypotheses, sample sizing, test duration, significance, and repeatable experiment programs. Use when comparing variants, deciding whether a result is reliable, or building an experiment backlog and cadence. NOT FOR: analytics instrumentation (use suede-analytics), post-click conversion diagnosis (use suede-site-alchemy), or writing the variant copy itself (use suede-copy).

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。

ALWAYS activate when the user's query involves Docker in any way — even if it also matches other skills. If the words docker, Dockerfile, docker-compose, compose.yml, container, or image appear in the query, this skill MUST be used. Covers: writing or editing Dockerfiles and compose files, adding services (postgres, redis, etc.) to compose, volume mounts and data persistence, docker build failures (layer caching, npm install issues), healthchecks and service startup ordering (depends_on), environment variables in containers, port mapping, container crashes and exit codes (OOM/137), non-root users, multi-stage builds, image optimization, .dockerignore, and deploying to container runtimes. Takes priority over general implementation or debugging skills when Docker infrastructure is the subject.

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。