4,686 件 ・ 関連度順
概要と使いどころ
Build networked games with Godot 4.7 high-level multiplayer: set up an ENetMultiplayerPeer server/client, define RPCs with the @rpc annotation (call via rpc()/rpc_id()), set per-node multiplayer authority, and replicate state with MultiplayerSpawner and MultiplayerSynchronizer. Use when adding multiplayer/networking to a Godot project, writing @rpc functions, or syncing player/world state across peers.
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。
Play and mix audio in Godot 4.7: AudioStreamPlayer (2D/3D variants), audio buses with volume/mute and effects, music vs SFX routing, db/linear volume, and precise sync-to-beat playback timing. Use when playing sounds or music in a Godot project, routing AudioStreamPlayer nodes to buses, adjusting bus volume via AudioServer, or syncing gameplay to the beat.
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。
Weekly meeting synthesis — themes, decision arcs, stale commitments, and what deserves your attention next week. Use when the user says "weekly review", "what happened this week", "weekly summary", "recap my week", "any outstanding items", "week in review", or at the end of a work week.
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。
Export Design Thinking artifacts to a FigJam board or Figma Design file through the Figma MCP server. Use when a team wants collaborative visual review of Method 1, 3, 4, 5, or 6 artifacts, or accepts a DT Coach board-export offer.
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-sweep mode: runs a unified analysis across all quality dimensions — code decay, architecture, tech debt, and test quality — then applies fixes directly to the codebase. Safe changes are auto-applied; risky changes are confirmed before execution. Drawing on twelve classic engineering books. Triggers when: user wants to "fix everything", "sweep the codebase", "auto-fix all issues", "clean up the whole project", or asks for a single command that both diagnoses and remediates quality problems. Do NOT trigger for: read-only audits or health reports where the user only wants findings without code changes; single-dimension reviews (use the focused skill instead: brooks-review / brooks-audit / brooks-debt / brooks-test); server health checks, HTTP /health endpoints, Kubernetes probes, database health, or application uptime.
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。
Tech debt assessment that identifies, classifies, and prioritizes maintainability problems — helping teams build a refactoring roadmap — drawing on twelve classic engineering books. Triggers when: user asks about tech debt, refactoring priorities, what to clean up first, or asks "why is this so hard to change?", "what should we fix first?", or "how do I justify refactoring to management?". Do NOT trigger for: server health checks, HTTP /health endpoints, Kubernetes probes, database health, or application uptime — "health" in those contexts is infrastructure, not code quality. Also not for single-function refactoring questions.
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。
Combined codebase health dashboard that scores a project across all four quality dimensions — PR quality, architecture, tech debt, and test quality — in a single pass, drawing on twelve classic engineering books. Triggers when: user wants an overall quality assessment, asks "how healthy is this codebase?", "run all the checks", "I need a health score before the release", or wants to onboard a new team with a quality overview. Do NOT trigger for: server health checks, HTTP health endpoints, Kubernetes liveness/readiness probes, database health, or application uptime. Also do not trigger when the user specifically requests only one dimension — use the corresponding focused skill instead (brooks-review / brooks-audit / brooks-debt / brooks-test).
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。
Diagnoses macOS system-level slowness, heat and fleet-wide timeouts: high load average, leaked per-session child processes (MCP servers, helpers), fork storms, busy loops. Use when the Mac feels slow or hot, fans spin up, or everything times out at once (电脑发烫/卡顿/负载高/全部超时). Not for single-app bugs, network slowness (use tunnel-doctor), launchd watchdog design (use macos-watchdog), or disk-full (use macos-cleaner).
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。
Converts a PDF into one self-contained, readable HTML file that preserves images, tables, charts and reading order — optionally translating it into another language while keeping every figure. Uses structured extraction (PyMuPDF), font-size-driven layout, compressed base64-inlined images (a single portable file), and mandatory headless-Chrome visual verification. Use whenever someone wants to READ a PDF as a web page or clean document, turn a PDF into HTML, or translate a PDF into another language while keeping its images/tables/charts intact — e.g. "PDF 转 HTML", "把这个 PDF 转成中文网页版", "make this report readable", "translate this PDF but don't lose the charts", "I just want to read this PDF on my phone". Distinct from doc-to-markdown (plain Markdown text) and pdf-creator (Markdown→PDF) — this one produces a styled, image-faithful HTML reading experience.
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。
Audits, preserves and recovers local Git state before cleanup: unpushed or wrong-branch commits, dirty worktrees, duplicate clones, stashes, dangling commits, squash-merge uncertainty. Use when the user fears lost work, wants to recover a commit, asks if a branch is actually merged, asks whether a branch, worktree or clone is safe to delete, or wants one clean main (误删分支 / 还有没有丢的东西). Not for GitHub PR operations.
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。
Keep Claude Code sessions productive across resets with output filtering, session logging, and auto-resume. Use when starting a long or complex coding session, when previous sessions lost context mid-task, or when you need Claude to resume exactly where it left off after a reset. Produces a session.log at the project root, filtered command output that preserves context, and automatic resume of in-progress tasks after any reset.
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 a fast, honest competitive scan — the dimension table built from public evidence (sites, docs, pricing pages, changelogs, reviews), the claims-vs-observed discipline, and the so-what synthesis that ends in moves, not a landscape mural. Use when asked what are competitors doing, quick scan of these three rivals, how does our pricing/feature set compare, or prep the competitive slide honestly. Produces the evidence-based comparison table, the marketing-vs-reality flags, the so-what synthesis, and the staleness date.
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。
Fit a retention curve to observed cohort data and project LTV — computed, not estimated. Use when someone has real cohort retention numbers (month 0, 1, 2…) and asks what lifetime value, lifetime periods, or long-run retention they imply, or whether retention is flattening or leaking. Produces a fitted power curve (parameters, R², retention floor), a 24-36 period projection, and a real .xlsx with live formulas where editing ARPU recalculates LTV — via the bundled zero-dependency script.
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 a real brainstorm — divergent generation without judgment, then convergent selection with explicit criteria — instead of listing ten obvious ideas and calling it creativity. Use when asked to brainstorm, generate ideas or options, explore a solution space, or name something. Produces a genuinely wide option set (including the weird tail), then a shortlist selected against named criteria with the rejects preserved.
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 and deliver a raise request that actually works — the evidence, the number, the timing, and the exact words — instead of hoping it gets noticed. Use when asked how do I ask for a raise, I deserve more money, prepare me to ask for a raise, or negotiate a pay increase at my job. Produces a value case built on your actual contributions and market rate, a specific target number with justification, the right timing and person, a script for the conversation, and responses to the likely pushbacks — turning 'I want more' into a business case your manager can say yes to.
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 transition from a pure self-serve model to a hybrid motion that uses human sales to capture large enterprise deals while maintaining a frictionless product entry point.
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。
Convex backend development guidelines. Use when writing Convex functions, schemas, queries, mutations, actions, or any backend code in a Convex project. Triggers on tasks involving Convex database operations, real-time subscriptions, file storage, or serverless functions.
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 working with icons in any project. Provides CLI for searching 200+ icon libraries (Iconify) and retrieving SVGs. Commands: `better-icons search <query>` to find icons, `better-icons get <id>` to get SVG. Also available as MCP server for AI agents.
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。
Check a Framer project's Server API connection: verify the per-project API key with the official handshake. Trigger phrases: framer, framer api, framer 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。
Official public OpenMeld Skill for agents using the `openmeld` CLI to consult the Center Agent, set up OpenMeld, connect local agents, create or request Agent Profiles, work in Organizations and Spaces, observe or stop Wakes, trace delivery, and repair local 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。
Guides an agent through reproducing, root-causing, fixing, and validating flaky tests in the PostHog monorepo. Use when a test fails intermittently in CI but passes on rerun or locally, when `hogli ci:insights` or the debugging-ci-failures skill classifies a failure as a flaky test, when given a GitHub Actions URL for a flaky job, when asked to check Trunk Flaky Tests for a test, PR, or master, or when asked to deflake, stabilize, or fix a flaky Jest, pytest, or Playwright test. Core discipline: reproduce locally before changing anything, fix the root cause (never mask it with sleeps, retries, or bigger timeouts), and prove the fix with an N-run validation loop sized to the observed failure rate. Stabilizing is not the only valid outcome — the skill also gates whether the test should exist, so deleting a test that catches nothing real, or re-leveling one that flakes because of the level it runs at, are first-class endings.
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。
Context-aware translation that preserves tone, style, and natural word order. Use when translating UI strings, documentation, marketing copy, or any multilingual content. Infers register, domain, and style from the source text and surrounding codebase context.
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。
Implement server APIs, authentication, and application data access. Schema modeling and query tuning use oma-db.
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。
Backend specialist for APIs, databases, authentication with clean architecture (Repository/Service/Router pattern). Use for API, endpoint, REST, database, server, migration, and auth work.
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。