241 件 ・ 関連度順
概要と使いどころ
Add Stripe payment processing to Next.js projects. Implement checkout sessions, payment handling, subscriptions, webhooks, and customer management. Use when adding Stripe to a Next.js project, building payment flows, implementing subscriptions, or integrating payment processing.
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 implementing Stripe webhook endpoints and getting 'Raw body not available' or signature verification errors - provides raw body parsing solutions and subscription period field fixes across frameworks
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 Stripe integration decisions across API selection (Checkout Sessions vs PaymentIntents), Connect platform setup (Accounts v2, controller properties), billing/subscriptions, tax and registrations (Stripe Tax, automatic_tax, product tax codes), Treasury financial accounts, integration options (Checkout, Payment Element), migrating from deprecated Stripe APIs, and security best practices (API key management, restricted keys, webhooks, OAuth). Use when building, modifying, or reviewing any Stripe integration, including accepting payments, building marketplaces, integrating Stripe, processing payments, setting up subscriptions, collecting sales tax, VAT, or GST, creating connected accounts, or implementing secure key 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。
Operate the Resend platform from the terminal — send emails (including React Email .tsx templates via --react-email), manage domains, contacts, broadcasts, templates, webhooks, API keys, logs, automations, and events via the `resend` CLI. Use when the user wants to run Resend commands in the shell, scripts, or CI/CD pipelines, or send/preview React Email templates. Always load this skill before running `resend` commands — it contains the non-interactive flag contract and gotchas that prevent silent failures.
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。
Implement Stripe payment processing for robust, PCI-compliant payment flows including checkout, subscriptions, and webhooks. Use when integrating Stripe payments, building subscription systems, or implementing secure checkout flows.
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 analyzing an existing TypeScript or JavaScript codebase to decide where and how to introduce Inngest. Covers repository discovery, framework and package detection, finding durability gaps in HTTP handlers, webhooks, cron jobs, queues, long-running jobs, AI agents, Agent Evals, polling loops, eval loops, and side-effect-heavy code, then producing and implementing an incremental integration plan.
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 operating Inngest API resources from the terminal with `npx inngest-cli@latest api`: Cloud/local run debugging, event-run lookup, function traces, function invocation, app syncs, webhooks, environments, keys, account checks, and Insights queries. Provides prescriptive command routing for agents: which CLI command to run for a run ID, event ID, app ID, function ID, Cloud environment, API key, missing ID, or potentially mutating operation. Use `inngest-cli` for dev server setup/general CLI workflows and `inngest-api` only when raw REST API v2 docs or OpenAPI fallback are needed.
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 event-driven workflows, decoupling services, implementing fan-out patterns (one trigger, many downstream handlers), implementing idempotent event handling with IDs (24-hour dedupe window), or handling at-least-once delivery from external sources like Stripe webhooks. Covers Inngest event schema, payload format, naming conventions, IDs for idempotency, the ts param, fan-out patterns, and system events like inngest/function.failed.
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 email features, emails going to spam, high bounce rates, setting up SPF/DKIM/DMARC authentication, implementing email capture, ensuring compliance (CAN-SPAM, GDPR, CASL), handling webhooks, retry logic, making emails accessible (alt text, headings, contrast, screen readers), or deciding transactional vs marketing.
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 Argilla 2.x for human-feedback dataset annotation, Python SDK dataset workflows, server deployment/operations, webhooks, and legacy v1/Rubrix migration.
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。
Email infrastructure for AI agents. Create accounts, send/receive emails, manage webhooks, and check karma balance via the AgentMail API.
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 AI phone agents with AgentPhone API. Use when the user wants to make phone calls, send/receive SMS, manage phone numbers, create voice agents, set up webhooks, or check usage — anything related to telephony, phone numbers, or voice AI.
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。
Threat-model product features, APIs, data flows, secrets, permissions, supply-chain changes, auth boundaries, and risky code paths before or during implementation. Use when touching authentication, authorization, payments, secrets, user data, uploads, webhooks, admin tools, innerHTML/eval/exec, dependency upgrades, or cross-tenant access.
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。
Fix silent failures in Fastly Compute@Edge when using send_async for fire-and-forget requests. Use when: (1) Background tasks (migrations, webhooks, notifications) triggered from Compute never complete, (2) send_async PendingRequest is immediately dropped, (3) Fire-and-forget pattern works locally but fails in production, (4) An async trigger "logs as triggered" but the target service never receives the request (especially after renaming backend constants — the URL hostname is cosmetic, the backend name determines routing, so a global rename can silently reroute calls to the wrong service). Also covers silent backend-not-found errors when FALLBACK_BACKENDS or other backend constants reference names not configured in the Fastly dashboard.
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。
Integrates payment processing with Stripe, PayPal, or Square including subscriptions, webhooks, and PCI compliance. Use when implementing checkout flows, recurring billing, or handling refunds and disputes.
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。
This skill should be used when the user asks to "upload images to Cloudflare", "implement direct creator upload", "configure image transformations", "optimize WebP/AVIF", "create image variants", "generate signed URLs", "add image watermarks", "integrate with Next.js/Remix", "configure webhooks", "debug CORS errors", "troubleshoot error 5408/9401-9413", or "build responsive images with Cloudflare Images API".
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 Xquik to fetch X (Twitter) data or act through a connected account: search, profiles, followers, replies, threads, timelines, media downloads, bulk exports, trends, monitors, signed webhooks, draws, posts, likes, follows, DMs, and AI analysis of posts (sentiment, brand mentions, news, market signals, viral score, custom labels). Also use for hashtag or @handle tracking when no other network is named, Xquik MCP setup, pricing, and X API comparisons. Skip data from other social networks, code that stays on the official X API (such as tweepy with an X developer bearer token), official X widget implementation, and content drafting or analysis without an API task. Not affiliated with X Corp.
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。
Operate AudioShake's cloud source-separation service (developer.audioshake.ai) to split a recording into stems. Use when a task involves isolating vocals, drums, bass, guitar, piano, keys, strings, or winds from music; separating dialogue / music / effects (DME) for film-TV post-production, localization, and dubbing; splitting a mixed recording into one stem per speaker; lyric transcription or word-level alignment; music detection/identification; or speech denoise/dereverb. Covers the Tasks API job lifecycle (assets, targets, formats, polling vs webhooks, credits, limits), choosing which stem targets a production actually needs, reviewing separated stems for bleed / artifacts / transient smearing / phase problems and repairing them, the rights and consent questions raised by separating copyrighted or third-party recordings, and the decision boundary for when a local open model such as Demucs is the better route than the API. Not for generating or synthesizing new audio, mixing, or mastering.
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 when an agent needs AssemblyAI for speech-to-text or speech-understanding work in media production, including pre-recorded, synchronous short-file, and real-time streaming transcription; speaker diarization or speaker identification; captions and subtitles; timestamps; language detection, code-switching, or transcript translation; audio intelligence such as summaries, chapters, topics, entities, key phrases, sentiment, content moderation, profanity filtering, and PII redaction; webhooks, scaling, rate limits, retention, security, consent, and QA for podcasts, interviews, captions, call recordings, and edit workflows.
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 ElevenLabs Scribe for speech-to-text production workflows: transcribing audio or video files, diarization and speaker/channel handling, word/character timestamps, captions/subtitles, keyterm prompting, entity detection/redaction, webhooks, realtime STT boundaries, pricing/limits, privacy/retention, consent, artifact custody, and QA for podcasts, interviews, edits, accessibility captions, and localization prep.
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。
Select, integrate, and operate multi-model video-generation gateways — hosted inference aggregators such as fal.ai, Replicate, and WaveSpeed that expose many third-party video (and video-adjacent audio) models behind one account, one API surface, and one bill. Use when deciding whether to route video generation through a gateway versus a direct model-provider API; when comparing gateways on catalog, async/queue job design, webhooks, pricing, schema discovery, and version pinning; and when operating gateway workloads in production — spend controls, retries, cross-gateway failover, content- safety differences, data retention, and commercial-rights passthrough of the underlying model. Not for direct model-provider APIs, local/self-hosted inference, model training/fine-tuning, or image-only gateway use.
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。
Produce 3D assets with Meshy (meshy.ai) through its REST API and web platform — text-to-3D, image-to-3D, multi-image-to-3D, AI texturing/PBR, remesh/topology control, UV, and auto-rigging/animation. Use this skill when an agent must generate a mesh from a prompt or reference image, control polygon count and topology, apply or restyle textures, rig a humanoid for animation, export to GLB/FBX/OBJ/USDZ/STL for Unity/Unreal/Blender, drive Meshy's asynchronous job API (auth, polling, streaming, webhooks, credits, rate limits), review generated meshes for game/film/print readiness, or decide whether Meshy is the right tool at all. Not for editing an existing hand-modeled asset's geometry, hard-surface CAD with exact dimensions, or guaranteed-watertight manufacturing parts.
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 AI lip sync and visual dubbing with Sync Labs (sync.so) — choose the right model (sync-3, lipsync-2, lipsync-2-pro, lipsync-1.9.0-beta, react-1), build the POST /v2/generate request, host inputs, handle async jobs via polling or webhooks, run batch dubbing/localization, and review output for sync accuracy and identity preservation. Use when an agent must re-voice, dub, translate, personalize, or re-time the mouth of a talking-head video (or animate a still face from audio), or must debug a failed/rejected Sync generation. Also covers consent, likeness, and rights obligations for editing a real person's face.
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 operate rights-aware Bria FIBO and FIBO Lite image-generation workflows with structured prompts, reference images, asynchronous status handling, webhooks, cost gates, and safe artifact downloads. Use when a user asks for Bria/FIBO generation, refinement, inspiration, reproducibility, hosted API integration, or a licensed-data image workflow; do not use for FIBO Edit, video, generic image editing, or third-party FIBO gateways.
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。