「eac」の検索結果

Trigger when: (1) the user mentions "noise", "slop", "frame audit", "video review", "letter spacing", "padding intrusion", "frame extract", "naive arrow", or Korean equivalents (노이즈, slop, 프레임 검수, 글자 깨짐), or (2) after rendering a new or modified Manim scene, or (3) the user asks to review an mp4 in `media/videos/` or `~/Downloads/`. Post-render audit workflow for Manim 1080p60 videos. Extracts keyframes via ffmpeg, inspects them through Claude Code's Read tool, and classifies any defects into four standing categories (naive arrow / padding intrusion / glyph kerning drift / frame-order error). Catalogues 12+ verified incidents across the four GEODE scenes so each is caught the first time, not rediscovered. The companion authoring skill is [[manim-scene-craft]].

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。

Runs the full implement-and-commit loop over a task list — selects the next incomplete sub-task, implements it, runs linters and tests, marks it done, commits, and repeats until the list is finished. Use when asked to work through a feature's task list at .ai/[feature]/tasks.md unattended, or to keep going until every sub-task is complete. For a single sub-task with no commit, use task-implementation; to stop for approval between each one, use iterative-development.

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。

Structures git branches and worktrees: keeps unrelated changes on separate branches, isolates each in its own worktree created so the repository's setup runs, records dependencies with git-machete, and recombines them into a temporary mixdown branch for local testing. Use before creating any branch or worktree in a codebase that works on more than one branch, including branching off the default branch to start a change; when starting work in a fork, clone, or third-party checkout; when choosing what a new branch should be based on; when a branch is growing a second unrelated concern; when deciding whether to stack branches or keep them independent; when preparing a change for a pull request or patch submission; when handed an existing worktree or branch to implement and commit in a fork; or when a local build needs several in-progress branches combined. Not needed where the repository clearly commits everything to the trunk, or holds notes or personal data rather than code.

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。

Grind through ready beads in priority order by running several issues at once, each in its own isolated git worktree managed by worktrunk (`wt`), then merging the finished branches back one at a time. Use when asked to work the beads queue in parallel, to run N issues concurrently, or when a serial grind is too slow and the ready issues are independent.

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。

Route frontend tasks to the right library skill. Detects React/Vue/CSS intent and returns specific skill file paths.

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 reference for inter-process communication mechanisms -- every way processes can talk on a computer. Covers sockets (TCP, UDP, Unix domain), WebSockets, SSE, pipes (named/anonymous), shared memory (mmap, shm_open), message queues, signals, D-Bus, XPC (macOS), gRPC, REST, stdin/stdout, file-based coordination, and clipboard. Performance benchmarks, platform availability, and code examples for each. Special focus on which IPC works best for AI agent coordination. Activate on: "IPC", "inter-process communication", "process communication", "how do I talk between processes", "Unix socket vs TCP", "shared memory", "named pipe", "WebSocket vs SSE", "gRPC vs REST", "agent coordination IPC", "XPC service", "message passing", "stdout pipe", "D-Bus", "mmap". NOT for: distributed systems design (use distributed-systems), network protocol design (use networking), message queue infrastructure like Kafka (use data-pipeline-engineer).

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。

Expert in visualizing and explaining braid theory, knot mathematics, and topological concepts for educational purposes. Use for creating interactive visualizations, explainer cards, step-wise animations, and translating abstract algebra into intuitive understanding. Activate on keywords: braid theory, knot visualization, σ notation, crossing diagrams, Yang-Baxter, topological education. NOT for general math tutoring, pure knot invariant computation, or non-educational knot theory research.

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 building server-driven UIs with htmx, designing hx-* attribute compositions, choosing swap strategies (innerHTML/outerHTML/morph), wiring out-of-band updates, integrating with form validation, or migrating from a SPA back to server-rendered HTML. Triggers: hx-get/hx-post setup, hx-target + hx-swap interplay, hx-trigger debouncing, OOB swaps for parts of the page outside the request target, response headers like HX-Trigger and HX-Push-Url, integration with Hyperscript or Alpine.js, accessibility considerations on partial updates. NOT for full SPAs (use React/Vue), framework-specific server libraries (use those skills directly), or non-HTML responses.

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。

Implementing the `Idempotency-Key` HTTP header pattern (Stripe-pioneered, IETF-standardizing) so retries don't double-charge or duplicate side effects — full Postgres schema with recovery-point state machine, fingerprint check, in-progress lock with 409 response, and 24h retention. Grounded in Stripe blog/docs, the IETF httpapi WG draft, and Brandur Leach's canonical implementation.

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。

Data structures and algorithms for AI agent episodic memory. Covers vector stores (HNSW, IVF, PQ), temporal indexing, knowledge graphs with triple stores, hierarchical summarization, forgetting curves, working/long-term/ procedural memory, and memory consolidation. Deep analysis of MemGPT/Letta, Zep/Graphiti, Mem0, and the Stanford generative agents memory architecture. Teaches the CS fundamentals behind how agents remember, retrieve, and forget. Activate on: "agent memory", "episodic memory", "vector search algorithm", "HNSW", "memory retrieval", "forgetting curve", "knowledge graph memory", "MemGPT", "Letta", "Zep", "Mem0", "memory consolidation", "temporal retrieval", "agent long-term memory", "memory layer". NOT for: conversation protocol design (use agent-conversation-protocols), agent infrastructure selection (use agentic-infrastructure-2026), building RAG pipelines (use ai-engineer).

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 resilient React error handling with Error Boundaries, Sentry integration, recovery UI, retry patterns, and graceful degradation. Activate on: error boundary, crash recovery, Sentry, error fallback UI, retry logic, unhandled exceptions. NOT for: form validation errors (use form-validation-architect), API error codes (use api-architect).

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。

Architect data fetching with TanStack Query v5, SWR, optimistic updates, prefetching, and cache invalidation strategies. Activate on: React Query, SWR, optimistic updates, cache invalidation, prefetching, stale-while-revalidate, infinite queries. NOT for: REST API design (use api-architect), database queries (use database skills), GraphQL schema (use graphql-expert).

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。

State-of-the-art data visualization for React/Next.js/TypeScript with Tailwind CSS. Creates compelling, tested, and accessible visualizations following Tufte principles and NYT Graphics standards. Activate on "data viz", "chart", "graph", "visualization", "dashboard", "plot", "Recharts", "Nivo", "D3". NOT for static images, print graphics, or basic HTML tables.

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。

Decompose DAGs into execution chains using width bounds, stratification, virtual nodes, and matching. Use when minimizing workflow lanes in dependency graphs. NOT for cyclic graphs, generic scheduling, or one-off queries with no preprocessing payoff.

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 the practical path from 'we have no design system' or 'we have a mess' to a real, functional design system. Component inventory, design token extraction, headless UI adoption (Radix, React Aria, Headless UI), migration order of operations, and the assessment-to-rollout pipeline. Activate on 'design system from scratch', 'bootstrap design system', 'no design system', 'design system migration', 'headless UI adoption', 'component audit', 'design token extraction', 'design system strategy'. NOT for building specific components once a system exists (use design-system-creator), not for generating token files/configs (use design-system-generator).

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。

Generates shell completion scripts for CLI tools. Parses command structure from help output, commander/yargs configs, or manual specification. Produces completions for bash, zsh, and fish that follow each shell's conventions.

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。

Android background task specialist for WorkManager, Foreground Services, Doze mode, and battery optimization. Activate on: WorkManager, background task Android, Foreground Service, Doze mode, battery optimization, periodic work, background sync Android, JobScheduler. NOT for: iOS background tasks (use swiftui-data-flow-expert), React Native background (use mobile-offline-sync-architect), UI architecture (use jetpack-compose-navigation-expert).

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。

Fundamental patterns for effective agentic behavior. Teaches decomposition, tool orchestration, error recovery, context management, quality self-assessment, and knowing when to stop. Model-agnostic principles that make any agent more effective regardless of domain. Activate on: "how should I structure this agent", "agentic workflow", "agent patterns", "multi-step task", "tool orchestration", "/agentic-patterns", "decompose this", "agent best practices", "chain of actions", "when should the agent stop", "agent loop design". NOT for: creating agent infrastructure (use agent-creator), building DAGs (use windags-architect), specific tool implementation.

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。

App Store and Google Play submission automator with Fastlane, screenshot automation, metadata management, and TestFlight/internal testing. Activate on: app store submission, Fastlane, TestFlight, Google Play Console, screenshot automation, metadata management, app review, code signing, provisioning profiles. NOT for: CI/CD pipeline setup (use github-actions-pipeline-builder), app architecture (use react-native-architect), analytics (use mobile-analytics-crash-reporting-expert).

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 building content-heavy sites with Astro, deciding between SSG/SSR/hybrid, choosing client directives (idle/visible/load/media), structuring content collections with type-safe schemas, integrating React/Vue/Solid/Svelte components in the same project, or migrating from Next.js for marketing/docs. Triggers: client:idle vs client:load tradeoffs, content collections schema with zod, image optimization via @astrojs/image, view transitions, server islands, MDX layouts. NOT for SPA-style apps that need full interactivity (use Next/Remix), Astro internals/plugin authoring, or non-content sites where islands provide no benefit.

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。

Systematically QA-tests a web app and fixes bugs: test, then iteratively fix, re-verify, commit each fix. Tiers: Quick, Standard, Exhaustive. Produces before/after health scores and fix evidence.

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。

Resolves an in-progress git merge/rebase conflict: reads conflict state, recovers each side's intent, resolves hunks, runs checks. NOT for the ship pipeline (mk:ship); NOT for bug debugging (mk:fix).

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。

Triages reviewer comments on a GitHub PR: verifies each against the codebase, then accepts/pushes back/clarifies, replies in-thread. NOT for reviewing (mk:review-pr); NOT for fixes (mk:fix).

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。

Vue 3 authoring/review: components, composables, reactivity, Pinia, Pinia Colada, file routing, forms. Composition API + script setup. Auto-activates on .vue files. Deep review: mk:vue-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。