「one」の検索結果

Drive one accepted change through implementation and checks to done, with one fresh review only where a mistake is costly. Use when: selected by name.

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。

Get one actionable improvement for your AI product based on the latest GenAI PM briefs. Fetch the last 5 days of curated AI PM insights from genaipm.com, analyze the current repo/project, find synergy between trending topics and the user's work, then research the source material and apply a concrete improvement. Use when the user wants to improve their AI product, get coaching on AI PM best practices, apply the latest industry insights to their codebase, or run "/one-step-better-ai-pm". Requires a GenAI PM subscriber email (set GENAIPM_EMAIL env var or provide when prompted).

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 components using ng-alain (@delon/abc) and ng-zorro-antd UI libraries. Use this skill when building enterprise UI features with ST (Simple Table), SF (Schema Form), ACL (Access Control), PageHeader, ReuseTab, and other @delon components. Ensures proper integration with ng-alain architecture, theming system, responsive layouts, and accessibility standards while following Angular 20 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。

Translate a complete mathematical modeling contest problem sentence by sentence into precise modeling language, preserve every substantive condition and definition, expose hidden constraints, draw a mandatory Mermaid cross-question flowchart, audit omissions, and deliver one easy-to-open Markdown report. For Huawei Cup (CPGMCM) graduate-contest problems, additionally prepend a plain-language layer that rewrites the background and questions as a primary-school word problem with a mandatory term-mapping table. Optionally render the finished report as one standalone HTML page on request. Use whenever a user supplies a CUMCM, CPGMCM, or other modeling problem and asks to interpret, translate, unpack, read closely, identify requirements, or avoid missing details before modeling.

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。

Neutral, framework-agnostic decision tree for project kickoff: "which agent / RAG / LLM framework should I reach for?" Synthesizes the ecosystem sections of 7 landmark-project SOPs (LangGraph, LlamaIndex, DSPy, CrewAI, vLLM, Aider, Dify) into one layered rubric. Core stance: frameworks are LAYERS, not competitors — a real project usually combines DSPy (compile) + LlamaIndex (retrieve) + LangGraph (orchestrate) + vLLM (serve), and you choose ONE per layer, not one to rule all. Use when starting any LLM/agent/RAG project, or whenever the "which framework?" question is asked. Deliberately neutral — unlike vendor docs and the LangChain-biased `framework-selection` on skill.sh, this skill has no horse in the race.

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 comprehensive component guideline documentation for SEED Design System. Use when creating or updating design guideline documentation in ./docs/content/docs/components directory. This skill helps create high-quality documentation similar to action-button.mdx.

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 accessible, composable UI with @base-ui/react primitives and project styling tokens. Use when creating or refining unstyled primitive components and behavior-heavy UI such as overlays, menus, popovers, dialogs, and form controls, or defining custom component APIs. Prefer the moai-library-shadcn skill when copied-in shadcn components are the primary implementation path.

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。

Assemble multiple plots into ONE publication-ready multi-panel journal figure (e.g. Figure 1 with panels A, B, C). Use whenever the user asks to combine, compose, or lay out several plots as a single composite figure — newly plotted from data or from already-rendered panels the user supplies (PNG/PDF). Ask the user to pick one of two approaches: (1) redraw every panel into one unified figure using independent, tightly packed `subfigures` (each sized to its own labels, so axes need NOT align), consistent style, correctly placed panel letters, and per-panel legends/colorbars; (2) composite already-rendered PNG/PDF panels onto a mosaic canvas and add panel letters (image compositing, not plotting). Both export vector PDF + high-DPI PNG. For a SINGLE plot from a data table, use the sibling `omics-plotting` skill instead.

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。

Provides complete shadcn/ui component library patterns including installation, configuration, and implementation of accessible React components. Use when setting up shadcn/ui, installing components, building forms with React Hook Form and Zod, customizing themes with Tailwind CSS, or implementing UI patterns like buttons, dialogs, dropdowns, tables, and complex form layouts.

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。

Provides comprehensive code review capability for React applications, validates component architecture, hooks usage, React 19 patterns, state management, performance optimization, accessibility compliance, and TypeScript integration. Use when reviewing React code changes, before merging pull requests, after implementing new features, or for component architecture validation. Triggers on "review React code", "React code review", "check my React 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。

Expert Next.js performance optimization skill covering Core Web Vitals, image/font optimization, caching strategies, streaming, bundle optimization, and Server Components best practices. Use when optimizing Next.js applications for Core Web Vitals (LCP, INP, CLS), implementing next/image and next/font, configuring caching with unstable_cache and revalidateTag, converting Client Components to Server Components, implementing Suspense streaming, or analyzing and reducing bundle size. Supports Next.js 16 + React 19 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。

Turns a screenshot, mockup, Figma export, or photo of a UI into working front-end code - React + Tailwind CSS v4 by default, or Next.js, Vue, or plain HTML/CSS - matching layout, spacing, colors, and typography, then renders the result and compares it against the image to close visual gaps. Use whenever the user shares an image of a website, app screen, dashboard, component, or wireframe and wants it built, cloned, recreated, or "made real", or says "code this up", "build this design", or "match this screenshot".

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。

Cleans up CRM data from HubSpot, Salesforce, Pipedrive, Zoho, Close, Attio, or any CRM CSV export. Finds duplicate contacts and companies with fuzzy matching (not just exact email), normalizes emails, phones to E.164, names, domains, states, and countries, flags stale, invalid, role, and test records, finds broken contact-company associations, and produces a reviewable merge plan plus import-ready files without touching the live CRM. Use this skill whenever the user wants to dedupe, find or merge duplicate contacts, merge companies or accounts, clean up a CRM, prep a CRM migration or re-import, or says the CRM export is a mess. Also use it when they mention only one symptom, like "the same person is in here three times", "half our leads are junk", or "our company records don't match".

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 design systems with tokens, components, and documentation. Use when building design systems, creating component libraries, or establishing design 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。

Install a complete design-token theme into any project in one pass -- pulls a style from the Open Agent Stack design-styles collection (aurora-mesh, cirrus, liquid-glass, mono-brutalist, neo-terminal, sand-terra, tidal) or a local tokens.json, wires it into Tailwind/CSS, and repaints existing components to match.

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。

Merges, appends, joins, and deduplicates multiple CSV, TSV, and Excel files (including multi-sheet workbooks) with pandas - mapping mismatched column names to one schema, normalizing keys, resolving conflicting values, tracking which file each row came from, and verifying the row math. Use when the user wants to combine spreadsheets or exports, stack monthly files, consolidate contact or lead lists, VLOOKUP-style join two sheets on an ID or email, or dedupe records across sources, even if they only say "put these together" or "clean up these lists into one".

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。

Honey for plain Claude — the terse-prose core with no agent-harness features. Paste into a claude.ai Project's custom instructions, a Style, or an API system prompt. Strips filler, hedging, and pleasantries from every response while keeping facts, names, numbers, steps, and code exact. No tools required.

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。

Honey benchmark scoreboard vs baseline and rival skills.

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 a diff for over-engineering and verbosity. Terse delete-list of what to cut and the lines each saves. One-shot.

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。

Compress-Cache-Retrieve for huge, repetitive array tool output (logs, scan results, time series, event streams) before it enters context. Keeps an informative sample — endpoints, anomalies/change-points, head/tail — drops the redundant rest to a local cache, and leaves a retrievable hash. Use when a tool returns a long uniform JSON array you must read but mostly skim, and the full set is one command away if needed. Lossy-but-recoverable.

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。

Rewrite a memory or context file (CLAUDE.md, AGENTS.md, a todo or notes file) into Honey-terse form so it costs fewer input tokens every session, without losing meaning. Backs up the original first. Use when asked to shrink or compress context files, trim CLAUDE.md, or cut per-session input cost. Prose only — never code, config, or data.

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。

Rewrite a memory or context file (CLAUDE.md, AGENTS.md, notes) into Honey-terse form to cut per-session input tokens. Backs up first.

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。

Delegate search- and review-heavy work to Honey's read-only subagents so large reads return compressed instead of bloating 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。

Inject Honey levers into dispatched subagent prompts.

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。