Plan and carry a Seedance video from brief through references, storyboard, generation handoff, shot-level review, and targeted repair. Use for an end-to-end Seedance production request; use a narrower prompt skill for a single prompt.
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。
LearnPrompt/awesome-seedance☆ 2,0712026年10月15日 更新
Diagnoses and reduces churn — cancellation flows, save offers, failed-payment recovery, at-risk detection, and the product and service causes underneath. Use this when churn is rising or unexplained, to design a cancellation or win-back flow, to recover involuntary churn, to identify at-risk accounts before they leave, or to decide whether a retention problem is a product problem.
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。
cbrock84/headcount☆ 2,0572026年9月18日 更新
Builds and maintains the design system a product is assembled from — tokens for color, type, spacing and elevation, component contracts, and the rules that keep them coherent as the product grows. Use this when starting a new interface, when screens have drifted apart visually, when the same component exists three times in slightly different forms, or when a token or component needs adding without breaking what exists.
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。
cbrock84/headcount☆ 2,0572026年9月18日 更新
Designs the joining and leaving experience — first-day readiness, ramp to productivity, knowledge capture, and clean exits. Use this to design or fix onboarding, shorten time to productivity, structure a leaver process, capture knowledge before someone leaves, or coordinate the access and asset steps around a joiner or leaver.
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。
cbrock84/headcount☆ 2,0572026年9月18日 更新
Establishes what a product is understood to be, for whom, and instead of what — then turns that into the messaging every other surface inherits. Use this when messaging is inconsistent across channels, when prospects misunderstand what the product does, when entering a new segment, when competitors are being compared against you unfavorably, or before any campaign, launch, or site rewrite.
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。
cbrock84/headcount☆ 2,0572026年9月18日 更新
Designs a coordinated multi-channel campaign or product launch around one story — objective, message, channel sequencing, timeline, assets, and the checklist that gets it out the door. Use this to plan a launch or campaign, sequence a go-to-market push, pressure-test a campaign before committing budget, or turn a product change into a coordinated set of activity. For ongoing channel programs rather than a bounded push, use `marketing-planning`.
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。
cbrock84/headcount☆ 2,0572026年9月18日 更新
Runs content as an operation — the production pipeline, editorial calendar, repurposing engine, competitive content intelligence, and audits of what already exists. Use this to build or fix a content production system, plan a calendar, decide how one piece becomes many, rank content ideas by expected impact, or audit an existing library for what to update, consolidate, or retire. For deciding what territory to own and why, use `content-strategy` 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。
cbrock84/headcount☆ 2,0572026年9月18日 更新
Decides where capital and attention go across business lines, products, and markets — what to fund, hold, harvest, or exit, and on what evidence. Use this to allocate budget across businesses, evaluate whether a product line should continue, decide whether to exit one, structure a portfolio review, or when several initiatives compete for the same limited investment.
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。
cbrock84/headcount☆ 2,0572026年9月18日 更新
Owns the customer's experience after the sale — support, success, escalation, and the feedback loop back into product. Use this for a decision spanning support and product, when service quality and cost are in tension, when deciding what to staff or automate, when a customer relationship is at risk above the account-manager level, or when nobody owns a recurring customer problem.
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。
cbrock84/headcount☆ 2,0572026年9月18日 更新
Builds the help center, in-product guidance, and knowledge base that let customers resolve problems without contacting anyone — content, findability, maintenance, and deflection measurement. Use this to build or fix a help center, reduce support volume, write documentation for customers, improve findability, or decide what deserves a help article versus a product fix.
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。
cbrock84/headcount☆ 2,0572026年9月18日 更新
Land a change everywhere the same fact is stated — enumerating the full surface inventory (landing copy, docs, machine-readable summaries, changelog badges repeated across every page, sitemap, README, descriptions embedded in code, and untyped frontend consumers of typed responses), generating a surface instead of restating it, drift tests where you cannot generate, never hand-maintaining a copy of a surface another codebase owns, shipping a paired PR when you change a format a different codebase decodes, and keeping overloaded product words apart. Use when adding or renaming a user-facing feature, editing product/marketing copy or docs, renaming a serialized response field, changing a serialization or share-link format, wiring one repo's output into another's checks, or reviewing a PR that touched only one place a fact appears.
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。
kajisho5/ffmpeg-skill☆ 1,9522026年10月15日 更新
Use this skill for planning, testing, and safely executing PostgreSQL schema migrations — especially when working with production data or shared databases. **Trigger when user asks to:** - Test a schema migration before applying it to production - Add, remove, or rename columns safely on a live table - Change a column's data type without downtime - Add or drop indexes, constraints, or foreign keys on large tables - Understand which ALTER TABLE operations lock the table - Roll back a failed migration - Plan a zero-downtime migration strategy - Fork a database to test a migration safely **Keywords:** migration, schema change, ALTER TABLE, add column, drop column, rename column, change type, zero downtime, lock, AccessExclusiveLock, concurrent index, forking, rollback, backfill, deploy Covers: lock-level reference for every common DDL operation, safe migration patterns, fork-based testing, zero-downtime column changes, index creation, constraint addition, backfill strategies, pre/post-migration validation, and rollback planning.
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。
timescale/pg-aiguide☆ 1,8692026年10月15日 更新
Scaffold a new design-product project that matches the recommended Claude Code layout (the reference structure). Use when starting a fresh product/app that will be built with this design system.
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。
plugin87/ux-ui-agent-skills☆ 1,7932026年10月11日 更新
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt 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。
rmyndharis/antigravity-skills☆ 1,7652026年10月15日 更新
Create production-ready Kubernetes manifests for Deployments, Services, ConfigMaps, and Secrets following best practices and security standards. Use when generating Kubernetes YAML manifests, creating K8s resources, or implementing production-grade Kubernetes configurations.
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。
rmyndharis/antigravity-skills☆ 1,7652026年10月15日 更新
Build production-ready monitoring, logging, and tracing systems. Implements comprehensive observability strategies, SLI/SLO management, and incident response workflows. Use PROACTIVELY for monitoring infrastructure, performance optimization, or production reliability.
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。
rmyndharis/antigravity-skills☆ 1,7652026年10月15日 更新
Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring. Use PROACTIVELY for ML model deployment, inference optimization, or production ML infrastructure.
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。
rmyndharis/antigravity-skills☆ 1,7652026年10月15日 更新
Für Product Counsel Workflow: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.
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。
Klotzkette/claude-fuer-deutsches-recht☆ 1,7072026年10月11日 更新
Für Product Counsel Workflow: prüft Frist, Form, Zuständigkeit und Eilbedarf; Ergebnis: Fristen- und Risikoampel.
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。
Klotzkette/claude-fuer-deutsches-recht☆ 1,7072026年10月11日 更新
视频内容逐字稿提取专用 skill。Use when the user provides a 抖音 or 小红书 URL and asks for逐字稿、视频转文字、听写视频或提取口播内容。Only extract transcript content; do not use this skill as the production subtitle clock, and do not summarize, rewrite, translate, title, or start production. Uses qushuiyin plus Paraformer ASR.
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。
Pluviobyte/rnskill☆ 1,6452026年9月21日 更新
End-to-end Chinese video washing pipeline. Use when the user provides a Bilibili, Douyin, Xiaohongshu, YouTube, web video URL, or local video file and asks for 视频洗稿, 视频二创, 洗稿并制作视频, 链接视频改写, 提取逐字稿后洗稿, or producing a new AI video from a source video. Orchestrates ra-逐字稿提取skill and ra-洗稿, ending at the 01-内容生产/视频工作台/待制作/ handoff queue; production continues through ra-video-production-director only on explicit request (直接制作/直接出片/一条龙).
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。
Pluviobyte/rnskill☆ 1,6452026年9月21日 更新
Use when preserving product intent, acceptance criteria, decision memory, open loops, roadmap context, or the product-manager continuity layer of an agent team.
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。
agentlas-ai/Agentlas-OS☆ 1,5842026年10月15日 更新
Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead 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。
microsoft/azure-skills☆ 1,5712026年10月15日 更新
Machine learning experimentation reference for model-experimentation conventions, experiment tracking and reproducibility, dataset and model abstractions, ML engagement fundamentals, and model-production readiness. Use when standing up ML experimentation infrastructure or assessing whether a trained model is ready for production.
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。
microsoft/hve-core☆ 1,5272026年10月15日 更新