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Store, retrieve, and pass credentials securely in MATLAB using the built-in MATLAB Vault (setSecret, getSecret, importSecrets, secretID) instead of hardcoding. Handles connections to any authenticated service: REST APIs, databases, cloud storage (S3/Azure/GCS), SFTP, and others. Covers API keys, tokens, passwords, SSH passphrases, CI/batch/scheduled jobs, and "keep credentials out of code" requests. Does NOT cover third-party secret managers (HashiCorp Vault, AWS Secrets Manager), OS-level key management, or the connection/query logic itself.

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 deploy edge functions with Cloudflare Workers and Wrangler. Use for APIs, cron jobs, and edge middleware.

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。

Fast path for a minimal CloudBase Web + database demo (最小前后端 / 最小可用 fullstack / Lovable-like BaaS). Defaults to @cloudbase/js-sdk client CRUD (NoSQL app.database / PG app.rdb), MCP-only schema, preview-first, and forbids cloud functions unless secrets, cron/background jobs, or logic that security rules/RLS cannot express. Use for 搭一套 demo、留言板、Todo、Notes、Kanban, or when users say 带云函数+云数据库 but only need CRUD. NOT for production multi-service backends, CloudRun, WeChat Mini Programs, or tasks that truly need server secrets.

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 this skill for Node.js backend AI via @cloudbase/node-sdk (>=3.16.0) — cloud functions, CloudRun, Express/Koa/NestJS, serverless APIs, scheduled jobs, LLM proxies, agent orchestration. The only SDK supporting image generation (ai.createImageModel + generateImage). Text via ai.createModel with groups cloudbase, hunyuan-exp, or custom-*; model ids (e.g. deepseek-v4-flash, glm-5, kimi-k2.6) go in the `model` field of generateText/streamText. MUST run two-step preflight before code — see body. NOT for browser/Web (use ai-model-web) or Mini Program (use ai-model-wechat).

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。

When the user wants to add or optimize structured data (Schema.org, JSON-LD). Also use when the user mentions "schema," "structured data," "JSON-LD," "rich results," "rich snippets," "Google rich snippets," "featured snippet schema," "add schema to page," "missing structured data," "schema validation error," "Schema Markup Validator," "Google Rich Results Test," "FAQ schema," "Article schema," "Organization schema," "JobPosting," "HowTo," "Event," "SoftwareApplication," "BreadcrumbList," "WebSite," "Recipe," "Product," or "Dataset." For SERP feature types and zero-click patterns, use serp-features. For AI search visibility strategy (not markup), use generative-engine-optimization. For HowTo step sections (placement, copy, vs FAQ), use howto-section-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。

When the user wants to set up, optimize, or manage LinkedIn Ads. Also use when the user mentions "LinkedIn Ads," "LinkedIn Campaign Manager," "Sponsored Content," "Lead Gen Forms," "Sponsored Messaging," "Message Ads," "Conversation Ads," "Accelerate," "Classic ad set," "Audience Network," "objective-based pricing," "Insight Tag," "job title targeting," "company targeting," "Matched Audiences," or "B2B paid ads." For organic posts, use linkedin-posts.

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。

Drive the Skills Manager CLI (`skm`) to initialize the hub, adopt unmanaged skills, list/enable/disable skills per AI tool, and doctor/fix symlink sync. Use whenever the user or an agent needs to manage skills from a terminal, SSH session, CI job, or headless machine; when a skill is missing in Claude Code, Codex, Cursor, Gemini, OpenCode, or any other supported tool; when asked to run skm / Skills Manager CLI; or when setting up Skills Manager without the GUI. Do not use for `npx skills` / skills.sh search (different CLI), for writing SKILL.md content (skill-creator), or for marketplace browse/install (not in skm).

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。

Builds and edits a model-driven Power Apps app from a natural-language intent — tables, columns, relationships, adaptive forms with sub-grids, views, Choice-column charts, business rules, business process flows, generative page intents for overview/dashboard surfaces (page `.tsx` generated in generate-pages after plan approval), and an app module + sitemap — via the headless cds-maker-sdk. Runs an interactive, multi-turn authoring flow (env selection, jobs-to-be-done first, then design-only App Spec authoring across confirmed levels, guardrail lint, plan-mode approval, generate-pages, full build) and a narrated build, and can download a deployed app back into an editable spec to change it. Use when the user says "build an app for X", "create a model-driven app", "make me an app to manage Y", "add a business process flow", or "edit/add to my app". This skill stands alone and does not require /genpage — but for a standalone generative page added to an app that already exists, use /genpage 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。

Use when one image must be composed from several reference pictures through the Scenario MCP server, each lending one thing: the character from one, the place, pose, style, light, palette, material, outfit, or layout from others. Also when a reference leaks into the result (its object, colors, or face showing where it should not) or a reference's role is ignored. Keywords: multi-reference, reference roles, combine references, style reference, pose reference, give each picture a job.

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 an agent drives Unity 6.3 (6000.3) on a Mac for any task: batch mode and -executeMethod jobs, a running editor (the user's GUI editor or a headless one), the Unity CLI and com.unity.pipeline, MCP servers, the Test Framework, command-line builds; when a batch run fails silently, 'Scripts have compiler errors', a capture comes back black or pink, or a result must be proven with numbers and a frame; or when a Unity brief must go to the right scenario-unity-* specialist.

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 an agent drives Godot 4.7 on a Mac for any task: headless --script jobs, --import, --check-only, command-line exports, GUT tests, windowed screenshots, the headless editor (-e) or an MCP server into a running editor; when a run hangs or fails silently, a capture is black, Godot 3 code breaks in 4.x, 'Identifier not found', export templates are missing; or when a Godot brief (2D, 3D, shaders, VFX, UI, multiplayer, export) must go to the right scenario-godot-* specialist.

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 an agent drives Unreal Engine 5.8 on a Mac for any task: Editor Python (the unreal module), headless UnrealEditor-Cmd -run=pythonscript jobs, Epic's Unreal MCP server, the Remote Control API, console commands and cvars; when a script breaks on 5.8 (EditorLevelLibrary, Remote Control calls refused, Substrate materials black, MRQ presets); when a level, material, shot or build must be judged by numbers and a screenshot before it is called done; or when a brief must go to the right scenario-unreal-* specialist.

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 or debugging Unity gameplay systems: enemy AI that patrols, chases and attacks, NavMesh baking and agents (AI Navigation 2), feet sliding on agents, state machines or behavior trees, physics projectiles that tunnel, the physics spiral, layers and the collision matrix, CharacterController vs Rigidbody characters, object pooling, 'hundreds of enemies', DOTS, Burst or Jobs decisions, Netcode for GameObjects multiplayer, audio mixers, snapshots, volume sliders and 3D combat sounds.

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 doing any Autodesk Maya task through Python or a bridge, headless or live: maya.cmds or OpenMaya 2.0 scripts, mayapy or maya.standalone batch jobs, a commandPort or MCP connection into a running Maya, "Maya 2027", validating or exporting scenes, or a maya.cmds script that fails after the 2025 to 2027 changes (PySide6, OpenPBR, renamed math nodes, removed flags). Also when a Maya model, rig, shot or render must be judged like a professional before it is called done, or a brief must be routed to the right Maya specialist.

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 connecting an AI agent to Scenario (scenario.com) through MCP, or when a task involves generating images, video, 3D, audio, sprites, textures, or game assets. Also when picking a Scenario model, running a LoRA, refining a generation prompt, uploading reference images, waiting on generation jobs, checking credits or quota, hitting Scenario auth, scope, or Forbidden errors, or setting up mcp.scenario.com in Claude Code, Cursor, VSCode, or another agent.

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 writing or fixing Maya pipeline code in Python: mayapy batch jobs over many scenes, validating and auto-fixing scenes, FBX export for Unreal or Unity (static, skeletal, animation clips, Game Exporter), Alembic or GPU caches, USD export, stages and layers, references and namespaces, PySide6 tool windows, OpenMaya 2.0 plug-ins, or slow playback. Also when an FBX lands with wrong scale, normals, tangents or extra takes, a USD export has one frame or smoothed meshes, or one bad file kills a batch.

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 generating or editing video on Scenario via MCP: text-to-video, a music video from a song, image-to-video (still animation, frame anchors), motion prompting, lipsync and talking avatars, dubbing a clip, video upscale to 4K, prompt-based editing, trim, split, concat, extend, reframe, resize, background removal, frame or audio extraction, long video jobs, or a clip over a duration limit. Keywords: txt2video, img2video, video2video, audio2video, I2V, T2V, V2V, localization.

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。

Plan and execute user research including research planning, recruiting, interview design, qualitative synthesis, and translating findings into product decisions. Use this skill whenever the user wants to plan user research, design interviews, recruit participants, conduct discovery, run formative research, or synthesize qualitative findings. Triggers on user research, UX research, user interviews, discovery research, generative research, formative research, qualitative research, user insights, research synthesis, recruitment, interview guide, jobs to be done. Also triggers when product decisions are being made without user input and the user wants to fix that.

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 Apex code, builds Lightning Web Components, optimizes SOQL queries, implements triggers, batch jobs, platform events, and Salesforce DX CI/CD pipelines.

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 Spark jobs, debugs performance issues, configures cluster settings for distributed data processing, DataFrame transformations, and structured streaming analytics.

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。

Validates dataset formatting and quality for SageMaker model fine-tuning (SFT, DPO, or RLVR). Use when the user says "is my dataset okay", "evaluate my data", "check my training data", "I have my own data", or before starting any fine-tuning job. Detects file format, checks schema compliance against the selected model and technique, and reports whether the data is ready for training or evaluation.

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 code that fine-tunes a base model using SageMaker serverless training jobs. Use when the user says "start training", "fine-tune my model", "I'm ready to train", or when the plan reaches the finetuning step. Supports SFT, DPO, RLVR, and RLAIF trainers, including RLVR Lambda reward function and RLAIF custom prompt creation.

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。

Tailor a resume to a job description by extracting keywords, scoring match, and rewriting bullets for impact. Use when applying to a role, optimizing for ATS keyword match, or customizing a cover letter.

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。

Talent acquisition across recruiting strategy, sourcing, interviews, and hiring analytics. Use when writing job descriptions, designing interview scorecards, analyzing hiring funnels, or improving offer acceptance rates.

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。