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Review GitHub pull requests with detailed, multi-perspective code analysis using parallel subagents. Use this skill whenever the user wants to review a PR, asks for code review on a pull request, mentions "review PR", "check this PR", "look at pull request", or references a PR number or GitHub PR URL. Do NOT use for local uncommitted changes — this skill only reviews pull requests on GitHub.

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。

When provisioning, setting a limit, or committing an estimate under uncertainty, size a buffer to residual error and the cost of breach—not to the optimistic edge.

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 a reference video and reverse-engineer its style into a reusable Seedance 2.0 prompting template. The output is a new skill/formula (like seedance-2-ugc.md) that captures the video's structure, pacing, camera work, edit style, and tone so it can be recreated with any product, any person, in any setting. Use this whenever someone provides a video they want to use as a style reference, says "I want to make videos like this", "deconstruct this video", "turn this into a template", "analyze this style", or drops a video file and wants to recreate that format repeatedly.

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。

Audit Git configuration with one read-only baseline command, then propose confirmed, non-destructive fixes for identity, editor, and diff and merge tooling, with signing and safe.directory help only on request. Use when setting up or checking Git on a workstation.

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。

Set up GitHub Copilot OpenTelemetry capture: configure the VS Code export settings, generate a local Grafana stack and dashboard, or generate the Azure collector, infrastructure, and dashboard for an organization.

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。

Drive Unity 6.3 LTS character animation with Animator Controllers: states, transitions, parameters, blend trees, animation layers, and humanoid Avatar IK. Use when wiring an Animator, setting parameters from script (SetFloat/SetBool/SetTrigger), building blend trees, or when the user mentions Animator, Mecanim, state machine, blend tree, or .controller.

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。

Add AI navigation in Unity 6.3 LTS: bake a NavMesh with the AI Navigation package (NavMeshSurface), move agents with NavMeshAgent.SetDestination, and handle dynamic obstacles. Use when setting up pathfinding, making an enemy chase the player, baking navigation, or when the user mentions NavMesh, NavMeshAgent, NavMeshSurface, NavMeshObstacle, or Unity pathfinding.

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 and control VFX in Unreal Engine 5 with Niagara: systems and emitters, modules and the spawn/update stages, exposed User parameters, and spawning or driving effects from Blueprints or C++. Use when building particle effects, NS_/NE_ assets, spawning a Niagara system at runtime, setting User parameters, or when the user mentions Niagara, VFX, or a particle system in Unreal.

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。

Build production Roblox interfaces with ScreenGui/PlayerGui lifecycle, responsive UDim2 layouts, safe insets, reusable editable Instances, cross-device input and selection, restrained motion, cleanup, and multi-viewport verification. Use for Roblox HUDs, inventories, shops, settings, ability bars, ScrollingFrames, AutomaticSize, GuiService, gamepad focus, touch UI, or UI that clips, resets on respawn, looks generic, or was generated as one giant LocalScript.

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 and build game UI/UX — HUDs, menus, and overlays — that survive every screen: anchor- based responsive layout, resolution/aspect scaling and safe areas, keyboard/gamepad focus navigation, a screen/menu state stack, and event-driven (not polled) HUD updates. Engine- neutral patterns that pair with the detected engine's UI skill. Use when the user mentions HUD, health bar, main menu, pause menu, settings screen, UI layout, anchors, UI scaling, aspect ratio, safe area, controller/keyboard menu navigation, or wiring UI to game state.

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。

Initialize evo for the current repository by exploring the codebase, proposing unexplored optimization dimensions, constructing the benchmark inside a baseline worktree, and running the first experiment. Use when the user invokes /evo:discover, mentions setting up evo, wants to instrument a codebase for autonomous optimization, or asks to start a new evo run on a project.

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。

Sets up and maintains isolated Claude Code CLI profiles to run Kimi, MiniMax, DeepSeek, GLM, StepFun or Anthropic in separate terminal windows. Use for multi-provider setup, switching models, csk/csd/csg aliases, CLAUDE_CONFIG_DIR, or ~/.claude-profiles. Owns profile-drift troubleshooting (missing skills/hooks, symlink drift, settings drift) and context-window setup ([1m] marker vs CLAUDE_CODE_MAX_CONTEXT_TOKENS).

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。

Configures and verifies an expanded, model-aware context window for OpenAI Codex CLI and Desktop. Use when Codex shows ~258K context, you want 500K or 1M tokens, auto-compaction fires too often, or model_context_window/model_auto_compact_token_limit needs repair. Not for changing the selected model or other Codex settings.

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。

Diagnose and resolve Claude Code plugin and skill issues. This skill should be used when plugins are installed but not showing in available skills list, skills are not activating as expected, or when troubleshooting enabledPlugins configuration in settings.json. Triggers include "plugin not working", "skill not showing", "installed but disabled", or "enabledPlugins" issues.

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。

This skill should be used when setting up, auditing, or enforcing internationalization/localization in UI codebases (React/TS, i18next or similar, JSON locales), including installing/configuring the i18n framework, replacing hard-coded strings, ensuring en-US/zh-CN coverage, mapping error codes to localized messages, and validating key parity, pluralization, and formatting.

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。

Configures and runs LLM evaluation using Promptfoo framework. Use when setting up prompt testing, creating evaluation configs (promptfooconfig.yaml), writing Python custom assertions, implementing llm-rubric for LLM-as-judge, or managing few-shot examples in prompts. Triggers on keywords like "promptfoo", "eval", "LLM evaluation", "prompt testing", or "model comparison".

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 asked 帮我定明年的个人 OKR, 写个人发展计划, IDP 怎么写, 明年目标怎么跟老板对齐, 个人 KPI 怎么定, 年初定目标, or plan next year's personal goals at a Chinese employer. Produces personal OKR or KPI drafts aligned upward to the team's goals with baselines, an individual development plan (个人发展计划) built on the 70-20-10 split, quarterly milestones and check-ins, and a script for the goal-setting conversation with the manager. For team or company OKRs use okr-builder; for reviewing the year just ended use cn-year-end-review.

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。

Build a smooth client-onboarding process that starts projects on the right foot — clear expectations, the info you need, and a professional first impression that prevents problems later. Use when asked to onboard a new client, create an onboarding process, kick off a client project, or client welcome packet. Produces a welcome and kickoff flow, the intake you need to start, expectation-setting on scope/comms/timeline/payment, a kickoff-meeting agenda, and the templates to reuse — so onboarding is consistent, not improvised, and prevents the scope and communication problems that sink projects.

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。

Set a boundary with someone — a friend, family member, coworker, or partner — clearly and kindly, with the actual words and a plan for the pushback. Use when asked how do I set a boundary with, I need to say no to, someone keeps overstepping, or help me set limits with. Produces a read on the boundary you actually need, a warm-but-firm script to state it (without over-explaining or apologizing it away), how to hold it when they push back or guilt-trip, and what to do if they don't respect it — because a boundary you can't state and hold isn't a boundary.

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 AI-authored code for its characteristic failure modes — plausible-but-wrong logic, hallucinated APIs, over-engineering, dead scaffolding, and silent security shortcuts. Use when reviewing an AI-generated or heavily AI-assisted PR, when AI-written code keeps shipping subtle bugs, or when setting review standards for a team using coding agents. Produces a focused review with AI-specific findings, verification steps per risk class, and a team checklist for AI-authored changes. For general PR review use code-review-checklist — this skill covers what that one assumes a human wouldn't do.

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。

Designs and implements testing strategies for any codebase. Use when adding tests, improving coverage, setting up testing infrastructure, debugging test failures, or when asked about unit tests, integration tests, or E2E testing.

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。

Implements error handling patterns, structured logging, retry strategies, circuit breakers, and graceful degradation. Use when designing error handling, setting up logging, implementing retries, adding error tracking, or when asked about error boundaries, log aggregation, alerting, or resilience patterns.

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。

Guides Docker, CI/CD pipelines, deployment strategies, infrastructure as code, and observability setup. Use when writing Dockerfiles, configuring GitHub Actions, planning deployments, setting up monitoring, or when asked about containers, pipelines, Terraform, or production infrastructure.

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。

Help users master their personal output by shifting from reactive scheduling to intentional energy management, internal trigger mastery, and proactive boundary setting.

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。