7,536 件 ・ 人気順
概要と使いどころ
Dashboard panel components (class-based, self-fetching) and push-update sidebar modules (functional, externally-driven) using vanilla TypeScript DOM API, with retry logic, localStorage persistence, and guarded CSS injection.
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。
Safely append CSS styles from one file to another, with per-selector grep verification after every append to catch silent truncation that tail or wc-l alone would miss
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。
Unified dashboard panel pattern combining circuit breaker resilience with enhanced UI features like retry logic, state persistence, and detailed error handling.
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-layer workflow for creating complete panel features by analyzing existing patterns and generating coordinated server routes, services, UI components, registration, and styling 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。
Multi-layer workflow for creating complete panel features by analyzing existing patterns and generating coordinated server routes, services, UI components, registration, styling files, AND explicitly wiring new handlers into the server's dispatch table (supports both Express middleware and manual http.createServer switch/case 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。
Writes and reviews structured Lean 4 proofs and designs Lean libraries following Mathlib conventions. Use when proving theorems in Lean, formalizing mathematics or specifications in Lean 4, defining new types or definitions in a Lean library, reviewing Lean proofs for readability and maintainability, refactoring long tactic proofs into lemmas, filling in sorry placeholders in a Lean development, setting up CI or linters for a Lean project, diagnosing slow proofs or maxHeartbeats timeouts, or writing custom tactics, macros, or linters.
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 improves fuzzing harnesses for C/C++ and Rust. Covers mapping raw bytes onto a target API, generating structured inputs, avoiding non-determinism and false crashes, and deciding what to fuzz together. Use when writing a first LLVMFuzzerTestOneInput or fuzz_target! harness, when a campaign finds nothing or reports crashes that will not reproduce, or when the target API needs structured rather than raw input.
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 reasoning about what survives compaction/context-loss/restart/seat-refresh, designing a high-fidelity restore packet, or distinguishing native runtime resume vs fork vs artifact-backed mental-model rebuild. Covers the 4 failure modes that prevent honest restore (compacted seat drops hot potato; restore packet preserves details but loses product intent; runtime resume mistaken for handover or fork; rebuilt seat starts with stale instructions).
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 classifying a slice closeout (auto-continue / human gate / park), routing a real decision to a human, or designing a human queue/dashboard surface. Treats humans as durable network participants with attention surfaces, queues, and decision records — escalation lands as a durable attention item, not a chat message. Approval is NOT required for every clean closeout; the default RSI conveyor continues unless an explicit human gate is reached.
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 UI mockups at three fidelity levels — ASCII wireframes for quick iteration, standalone HTML mockups for delivery with requirements, and live prototypes for interaction 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。
Use when reasoning about the rig lifecycle operations family (create / start / stop / resume / restore / snapshot / release / unclaim / destroy), reading or trusting `rig ps` / lifecycle projections after recovery, or designing proof for a lifecycle scenario. Covers the 4 failure modes (auto-restore creates partial rig; projections report healthier than reality; provider auth treated as impl work; resume succeeds for one runtime fails another) plus the restore-honesty rule (failed resume is FAILED loudly — no auto fresh fallback).
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 authoring rig specs, agent specs, workflow specs, startup/context fragments, operating-mode declarations, or designing the user spec library. Covers the 4 failure modes (spec instantiates topology but not workflow/mode; spec depends on local paths and fails on another host; agents modify specs as one-off files instead of preserving reusable intent; validation proves YAML shape but not whether topology can run) and the validation-vs-runtime-realization distinction.
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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
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 designing, building, operating, or diagnosing an ongoing application whose live backend or control loop includes OpenRig agents, including applications with a Markdown, YAML, or JSON agent control plane or a thin surface over specialist agent roles.
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-perspective review of a feature plan or requirements doc before development begins. Evaluates from strategy, design/UX, and engineering angles to catch gaps early.
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 designing multi-agent topologies that run ON OpenRig — authoring RigSpec and AgentSpec files for new rigs, creating agent startup content (guidance / skills / culture), or diagnosing why a launched rig's agents aren't behaving as intended. NOT for changing OpenRig itself (use developing-openrig); NOT for ordinary CLI operation of an existing rig (use openrig-user). Covers the full authoring lifecycle from user intent to validated, launchable rig.
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 custom metric packs for plugin-eval so teams can add local evaluation rubrics that emit schema-compatible checks and metrics. Use when the user wants their own evaluation criteria or visualizations.
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, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow by invoking the openai-docs skill or OpenAI developer docs MCP tools before generating 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。
Generate image-based alternatives, remixes, or new design directions from a Product Design brief. Use when the user asks for design variants, visual exploration, remixes, or image-generated approaches from provided 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。
Mandatory design-brief gate for clarifying the product and outcome. Use before ideation, image-to-code builds, redesigns, or product UI work to clarify missing product information and play back the brief before proceeding.
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 or plan bulk RNA-seq differential-expression analysis from count matrices with replicate, design formula, contrast, batch, normalization, QC plot, and result-table checks.
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 the user mentions MagicPath, designs, UI components, themes, canvas selections, or repo-to-canvas UI work; run magicpath-ai to search, inspect, install, or author components.
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。
`@expo/ui/swift-ui` package lets you use SwiftUI Views and modifiers in your app.
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。
**MANDATORY prerequisite** — you MUST invoke this skill BEFORE every `create_new_file` tool call. NEVER call `create_new_file` directly without loading this skill first. Trigger whenever the user wants a new blank Figma file — a new design, FigJam, or Slides file — or when you need a fresh file before calling `use_figma`. Usage — /figma-create-new-file [editorType] [fileName] (e.g. /figma-create-new-file figjam My Whiteboard, /figma-create-new-file slides Q3 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。