21st.dev Magic MCP — AI-powered UI component generation via natural language. Access to 21st.dev component library, SVGL brand logos, and real-time preview. Generate React/Tailwind components with /ui command.
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。
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概要と使いどころ
21st.dev Magic MCP — AI-powered UI component generation via natural language. Access to 21st.dev component library, SVGL brand logos, and real-time preview. Generate React/Tailwind components with /ui command.
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。
Natural, identity-preserving portrait retouching with a local CLI and a Busabase-backed review app. Use when the user asks to 美颜, 修人像, 磨皮, 提亮肤色, portrait retouch, headshot cleanup, profile-photo polish, before/after comparison, or batch portrait enhancement. Default to local non-destructive processing, preserve facial structure and skin texture, and require explicit approval before replacing or publishing any image.
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。
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
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。
Shape an article as a journey of beats, choose-your-own-adventure style. The user picks a starting beat from the raw material, you write only that beat, then offer options for where to pivot next, beat by beat, until the article reaches a natural end. Use when the user has raw material and wants to assemble it as a narrative rather than an argument.
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 a PostHog experiment reference from natural language to a concrete experiment ID by browsing `experiment-list` (not feature-flag tools), with disambiguation when multiple experiments match. Use when the user names or quotes an experiment ("split test demo", "the File engagement boost experiment", "onboarding retention test", "landing page hero experiment", "pricing experiment"), describes it loosely ("the signup experiment", "my pricing test", "the one with the new checkout"), uses a relative reference ("latest", "most recent", "the one I created yesterday"), filters by status (running, draft, stopped, archived), or otherwise refers to an experiment by anything other than its concrete ID.
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 analyzes stable-isotope-resolved metabolomics (SIRM / isotope tracing / fluxomics) experiments that measure metabolic ACTIVITY via 13C/15N/2H tracers, distinct from steady-state pool profiling. Covers tracer choice, isotopologue vs isotopomer, mass-isotopomer distributions (MID), fractional enrichment, the mandatory natural-abundance + tracer-purity correction (IsoCor, AccuCor), and the metabolic/isotopic steady-state vs non-stationary (INST-MFA) distinction. Use when feeding a labeled tracer and interpreting labeling patterns, correcting raw isotopologue intensities, computing or plotting an MID, or deciding tracing vs abundance profiling. For absolute pool concentration and MRM mechanics see metabolomics/targeted-analysis; for constraint-based genome-scale flux (FBA, not empirical tracing) see systems-biology/flux-balance-analysis; for feature detection see metabolomics/xcms-preprocessing; for pathway enrichment that ignores the pool-vs-flux caveat see metabolomics/pathway-mapping.
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。
Orchestrates group discussions between installed BMAD agents, enabling natural multi-agent conversations where each agent is a real subagent with independent thinking. Use when user requests party mode, wants multiple agent perspectives, group discussion, roundtable, or multi-agent conversation about their 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。
Manage MCP tools with natural language commands — list, enable, disable tools and tool groups
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 a new Scenic scenario (.scenic) from a natural-language description — "a car cuts in from the right lane", "a pedestrian crosses in front of the ego", "negotiate an unsignalized four-way" — by turning the request into a spec, generating the file from idioms proven on this build, and validating it by compiling and sampling before any simulator is involved. Use when the user asks to "write a Scenic scenario", "create a .scenic file", "turn this description into Scenic", "generate a scenario from text", or wants a Scenic scenario authored or repaired.
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。
Moves the CARLA spectator camera, frames an actor, or follows one live — third-person/chase, first-person/driver, top-down, or front views, resolving natural-language targets like "the ego" or "the Toyota Prius" to a specific actor. Use when the user asks to "move the camera/spectator", "watch/follow vehicle X", "3rd-person view of the ego", "1st-person view of the prius", "bird's-eye view", or "look at (x,y,z)".
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。
Explores a CARLA map's road network through the Map/Waypoint API — a natural-language rundown of the whole map ("give me the topology"), drawing the topology to confirm the modelled map matches the visible one, enumerating junctions to resolve phrases like "the 4-way junction in the middle", nearest-waypoint lane facts, and next/previous lane navigation. Use when the user asks about the map's layout, lanes, junctions, topology, or to locate/navigate specific map elements.
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。
Reads and sets the weather on a running CARLA server via get_weather/set_weather, and turns natural-language weather requests ("heavy rain at sunset", "light fog at night", "clear noon", "dust storm") into exact WeatherParameters — cloudiness, precipitation, puddles, wind, fog, sun position, wetness, dust. Use when the user asks to "set/change the weather", "make it rainy/foggy/sunny/night", "apply a weather preset", or describes any sky/lighting condition.
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 how an Agentforce agent extracts structured input parameters (slots) from a user's natural-language utterance to invoke an action. Triggers: 'agent extract date from user', 'agent action argument extraction', 'agentforce slot filling', 'agent invocable input mapping', 'agent fails to fill required parameter'. NOT for action authoring (use agentforce/agent-actions) or for prompt-template variable binding (use agentforce/prompt-builder-templates).
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。
Re-analyze an existing GitHub Issue using its current title and body, refresh the implementation plan against the latest code state, and update the Issue in place. Use when the user provides an Issue number (numeric, `#`-prefixed, or Issue URL) and wants to regenerate the code analysis via the explore-agent subagent. For reflecting comment-driven updates, use update-issue. For creating a brand-new Issue from a natural-language task description, use create-issue.
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 an implementation plan and a GitHub Issue based on the task description provided as an argument. Use this when the user supplies a natural-language task description (not an issue number) and wants a new implementation-ready Issue. If the input is an existing issue number, use create-issue-from-issue-number (re-analyze) or update-issue (reflect comments) 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。
Predict peptide-MHC class I binding and natural presentation with MHCflurry, NetMHCpan-4.1, and MixMHCpred to nominate candidate CD8 T-cell epitopes. Covers the binding-affinity (BA) vs eluted-ligand (EL/presentation) distinction, why %Rank beats raw nM for cross-allele work, the MS abundance bias that misranks low-expression neoantigens, allele-coverage inequity, and length bias. Use when scanning a protein or peptide set for class I epitopes, scoring neoantigen candidates, or choosing a binding predictor. For CD4/HLA class II see mhc-class-ii-prediction.
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。
Analyzes time-series and longitudinal RNA-seq for differential expression and trajectory structure. Covers DESeq2 LRT with reduced models, time as factor vs continuous vs natural splines, maSigPro (Nueda 2014 for RNA-seq), ImpulseDE2 with explicit impulse-model failure modes, DREAM for repeated measures via linear mixed models, pseudoreplication avoidance, conditional vs marginal modeling, and trajectory clustering with DPGP, Mfuzz (with Schwämmle 2010 fuzzifier estimation), and splines+k-means. Use when modeling time-course or longitudinal expression, choosing factor vs spline, handling repeated measures from the same subject, avoiding pseudoreplication, clustering temporal trajectories, or selecting between dedicated time-course tools and pairwise+LRT.
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。
SNS・UGC・日常スナップ風の自然な実写画像を生成する。参照人物の再現や、現在の場面を保った顔・体型補正にも使う。
Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.
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。
Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates 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。
Build natural-language crypto/DeFi agents and EVM MCP plugins (Claude Code, Cursor, Codex, Gemini). Aomi turns prompts into wallet-signed txs on Ethereum, Base, Arbitrum, Optimism, Polygon, Linea — non-custodial, fork-simulated. 40+ apps: Uniswap, Aave, Lido, Morpho, GMX, Hyperliquid, Polymarket.
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。
Geracao de imagens humanizadas via Google AI Studio (Gemini). Fotos realistas estilo influencer ou educacional com iluminacao natural e imperfeicoes sutis.
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 a single-file product landing page with a layered ASCII cosmos hero (rotating ASCII planet, drifting irregular asteroids, comet trails, nebula gas clouds — each in its own harmonious color) plus full marketing sections (about / features grid / showcase / spec / pricing / CTA / footer). Takes a natural-language description of one product (any kind — a note app, a coffee subscription, a CLI tool, an indie hardware, a hosting service…) and outputs ONE working .html file with deep-space dark or warm-letterpress theme. Runs in BOTH Claude Code (writes to ~/Desktop) and GLM / online chat (outputs HTML inline). Trigger phrases: "做个宇宙风产品落地页", "生成 ASCII 产品官网", "ascii-cosmos-gen ...", "做个独立软件 / 独立硬件落地页", or when user drags this skill folder into chat asking for an atmospheric product landing page.
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 a single-file VR-style portfolio website — works are tiled on the inside of a 3D cylinder/sphere (concave wraparound, like an immersive headset), with mouse-controlled head tilt, long-press to drag and browse the infinite canvas, click to open work detail. Includes overlays for About / CV / Contact / Filter. Takes a natural-language description of the studio and works (images + brief copy); outputs ONE working .html file. Runs in BOTH Claude Code (writes to ~/Desktop) and GLM / online chat (outputs HTML inline). Trigger phrases: "做个 VR 作品集", "做个无限画布作品集", "做个穹顶包裹的作品集", "vr-canvas-gen ...", or when user drags this skill folder into chat asking for a wraparound/immersive portfolio site.
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。