Optimize end-to-end application performance with profiling, observability, and backend/frontend tuning. Use when coordinating performance optimization across the stack.
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。
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概要と使いどころ
Optimize end-to-end application performance with profiling, observability, and backend/frontend tuning. Use when coordinating performance optimization across the stack.
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。
Discover AAS skills for an explicit task and compare their complete instructions without installing them.
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。
Turn 2+ user reference images into a high-fidelity animated Codex companion using PocketMen's own local stack. Prefer the open-weight Neural Local Studio (FLUX.2 klein 4B; optional Qwen-Image-Edit-2511 Identity-Max) on compatible hardware; otherwise fall back to the deterministic local renderer. Never require hatch-pet or OPENAI_API_KEY for the normal workflow.
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。
Conducts digital forensics investigations following a personal data breach, covering evidence preservation, chain of custody documentation, log analysis, scope determination, and root cause analysis. References industry-standard tools including Splunk, ELK Stack, and Wireshark. Provides forensic workflow from initial evidence collection through final investigation report. Keywords: digital forensics, breach investigation, evidence preservation, chain of custody, root cause analysis, Splunk, ELK, Wireshark.
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。
Discovers the core attributes of the current code repository and its projects — languages, frameworks, tooling, and where things live — and writes a concise reference section directly into the project's AGENTS.md or CLAUDE.md for other skills, agents, and hooks to consume. Use when scanning, analyzing, or detecting the project's technology stack, build tools, or repository structure. Does not create or update project documentation — use project-documentation for writing feature or system docs.
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。
Creates and maintains project documentation for features, systems, and components. Use when documenting how a feature, system, or component works — including writing, updating, or organizing docs. Does not scan or detect the project's technology stack — use project-discovery for repository analysis and config detection. Does not create architectural decision records — use architectural-decision-record for ADRs. Does not create or update coding standards — use coding-standard instead. Does not generate PR descriptions — use update-pr-description for that. Does not produce runbooks for operational scenarios — use runbook for that. Does not rewrite existing prose for readability — use edit-for-readability for that. Does not produce an ephemeral, understand-now overview of code or a PR — use code-overview for that.
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。
Remove signs of AI-generated writing from prose, and keep it out of a repo. Use when drafting, editing, or reviewing text to make it sound natural and human, or when auditing a whole docs folder for AI slop. Detects 41 patterns across content, language, style, communication, filler, and rhetoric, including: significance inflation, promotional language, -ing tails, vague attributions, AI vocabulary, copula avoidance, negative parallelisms, false agency, em dash overuse, chatbot artifacts, hedging stacks, staccato drama, and aphorism formulas. Includes voice calibration, a no-fabrication rule, statistical tells, and a draft -> audit -> final rewrite loop.
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。
Create original short videos using the 分层接力|小物体穿越多区域完成传递 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
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。
Modern TypeScript project architecture guide for 2025. Use when creating new TS projects, setting up configurations, or designing project structure. Covers tech stack selection, layered architecture, and best practices.
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 planning, building, designing, code review, refactor, fixing, improving, optimizing, enhancing, or checking UI/UX work. Covers product patterns, landing pages, chart choices, visual styles, palettes, typography, UX rules, and 9 stacks (React, Next.js, Vue, Svelte, SwiftUI, React Native, Flutter, Tailwind, shadcn/ui). Projects: website, landing page, dashboard, admin panel, e-commerce, SaaS, portfolio, blog, mobile app, .html, .tsx, .vue, .svelte. Elements: button, modal, navbar, sidebar, card, table, form, chart. Topics: color palette, accessibility, animation, layout, typography, font pairing, spacing, hover, shadow, gradient.
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 architecture foundations before implementation. Use when asked to design or refactor architecture, choose Rust/Go crate, package, module, runtime, workflow, or service boundaries, compare mature project architecture, prevent stacked one-off PRs, audit migration debt in existing repos, or produce a spec before coding.
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 this skill to diagnose CSS and frontend layout issues such as positioning, overflow clipping, Tailwind class conflicts, z-index stacking, and React rendering visibility problems.
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。
Modern Go Web application architecture guide. Use when creating new Go web projects, APIs, or microservices. Covers project structure, tech stack selection, and best practices based on Go standards.
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。
在已经过独立验证的 CLIProxyAPI upstream 之上部署 NewAPI 计费层,把 Codex/Claude/Gemini/Qwen 等订阅账号包装成可计费的 OpenAI 兼容 API。本 Skill 不负责新建裸 CLIProxyAPI;负责 NewAPI Docker 部署、容器到宿主桥接、模型计费倍率、参数化额度修正、多账号 OAuth 凭据热加载和双路径验证。当用户说“给现有 cliproxy 加 NewAPI”“配置 NewAPI 渠道接已运行的 cliproxy”“NewAPI 价格不对”“给现有部署加账号”“172.17.0.1 容器网络”或“408 冷却放大故障”时触发。
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。
Advanced content and topic research skill that analyzes trends across Google Analytics, Google Trends, Substack, Medium, Reddit, LinkedIn, X, blogs, podcasts, and YouTube to generate data-driven article outlines based on user intent analysis
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。
Fix macOS app hard crashes (EXC_CRASH / SIGKILL) caused by accessing TCC-protected APIs without the matching Info.plist usage description key. Use when: (1) App crashes immediately when touching Photos, Contacts, Calendar, Reminders, Location, Microphone, Camera, Screen Recording, etc., (2) Crash report shows `Exception: EXC_CRASH (SIGKILL)` with `Termination namespace: TCC`, (3) Crash stack includes `TCC.__TCC_CRASHING_DUE_TO_PRIVACY_VIOLATION__`, (4) Termination details contain "This app has crashed because it attempted to access privacy-sensitive data without a usage description", (5) Flutter macOS publish / gallery-save flow crashes on Gal.putVideo, PHPhotoLibrary, CNContactStore, etc. Critical distinction: macOS does NOT return a deny error — it SIGKILLs the process. This skill also covers the NSPhotoLibraryUsageDescription vs NSPhotoLibraryAddUsageDescription distinction that trips many apps.
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。
Separate a messy working tree with multiple tangled features into clean, focused PRs. Use when: (1) Working tree has uncommitted changes from multiple features mixed together, (2) Need to create a PR for just one feature from a mixed working tree, (3) "git stash pop" fails with "already exists, no checkout" for untracked files, (4) Pre-commit hooks block commits due to unrelated untracked files with errors, (5) Interface changes in one feature break consumer files from another feature in the same working tree. Covers git stash workflows, branch separation, conflict resolution, and pre-commit hook workarounds. Never stack PRs — always target main.
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。
Fix "setState() or markNeedsBuild() called during build" error triggered from deactivate(). Use when: (1) Error occurs during widget disposal or navigation away, (2) Stack trace shows deactivate -> some notifier -> ValueListenableBuilder._valueChanged, (3) Video/audio player pause() or stop() calls in deactivate() cause the error. The fix is deferring state-modifying operations to addPostFrameCallback.
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。
Run the mandatory verification stack when changes affect runtime code, tests, examples, or build and test behavior in the OpenAI Guardrails Python repository.
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。
Full-stack autonomous math modeling agent for MCM/ICM (美国大学生数学建模竞赛). Handles team control number, problem choice (A–F), English academic writing, mcmthesis LaTeX template, and optional practical deliverable (memo/letter/report). Use when the user provides an MCM/ICM problem and wants end-to-end automated modeling, coding, and paper generation in English.
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。
Full-stack autonomous math modeling agent for CUMCM (全国大学生数学建模竞赛). Reads the problem statement and data, iterates through research → coding → verification → LaTeX writing, and produces a publication-quality PDF paper. Use when the user provides a CUMCM problem and wants end-to-end automated modeling, coding, and paper generation.
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。
Assign, validate, normalize, and explain Luhmann/Zettelkasten-style project-note codes for Chinese book manuscripts, Obsidian Markdown folders, Mandala-Grid section files, HyperCard Markdown stacks, and project-note JSON to EPUB workflows. Use when Codex needs to scan folders for 部/章/節/項/目 numbering, generate stable card ids, insert branch codes without renumbering existing notes, map letter-coded branches to Obsidian Mandala sections, preserve K### keyword index cards, sanitize private catalogs into public examples, or prepare card IDs for EPUB and HyperCard output.
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。
Instrument programs (Python, C/C++, Java) to capture snapshots of key program states at runtime, including variables, memory, and call stacks. Use when you need to debug complex issues, reproduce test cases, prepare traces for formal verification, or analyze program execution. Supports manual instrumentation points, automatic function/method instrumentation, and conditional triggers. Outputs structured JSON snapshots for debugging, replay, and verification workflows.
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。
Analyze failing tests to detect functional bugs in code. Takes repository and failing test output as input, analyzes execution behavior, assertions, and stack traces to identify suspicious code regions and root causes. Use when debugging test failures, investigating regression bugs, or understanding why tests fail. Explains the bug mechanism, identifies affected code, and suggests fixes based on test expectations vs actual behavior.
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。