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Plan and run backups, set recovery objectives, and run disaster recovery drills. Use this skill when defining RPO/RTO targets, designing backup architecture, deciding what to back up and how often, planning for full-region or platform outages, or running a restoration drill. Triggers on backup, restore, RPO, RTO, disaster recovery, DR, business continuity, what if the database is gone, what if our hosting goes down, recovery drill, ransomware planning. Also triggers when an incident reveals a gap in restoration capability.

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Cross-format content adaptation. Turning one substantial piece into many derivative formats (blog series, email sequences, social posts, webinars, podcasts, video shorts) without losing the original's value or producing AI-slop variants. The discipline of adaptation per medium rather than mass-blast distribution. Triggers on content repurposing, content adaptation, cross-format content, content atomization, content multiplication, content distribution across formats, source-piece-to-derivative, video shorts from blog, email from whitepaper, podcast from article, blog series from research. Also triggers when a flagship piece is shipping but the team has not planned how to extend it across formats, when repurposing is happening but the derivatives feel mass-produced, or when AI-assisted repurposing is producing slop variants of strong source pieces.

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Audit and reduce infrastructure and tooling costs without sacrificing reliability or velocity. Use this skill when reviewing monthly cloud or SaaS spend, finding unused resources, rightsizing infrastructure, negotiating vendor contracts, deciding what to consolidate, or planning for budget cuts. Triggers on cost optimization, cloud spend, SaaS spend, rightsizing, unused resources, FinOps, infrastructure audit, vendor consolidation, budget cut, cost review. Also triggers when finance flags rising costs or when a contract renewal is up.

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Deploy to AWS Elastic Beanstalk, in either Beanstalk Standard mode (EC2) or Beanstalk Cluster mode (managed EKS). Triggers on: elastic beanstalk, EB, beanstalk standard, beanstalk cluster, managed EC2 platform, web app with managed patching, worker on EC2, Heroku alternative, don't want to manage servers or container orchestration, migrate from Heroku, managed operational lifecycle, containerised app without operating Kubernetes, several services sharing a managed cluster, managed EKS without kubectl. Covers web and worker applications on EC2, and containerised single- and multi-service applications on managed EKS.

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Data-driven Scrum Master for sprint health scoring, Monte Carlo velocity forecasting, retrospective analysis, capacity planning, and Tuckman team coaching. Use when facilitating sprint planning, diagnosing velocity, or running retrospectives.

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Design tokens, light/dark theming, and WCAG contrast validation for HTML documents and decks, compiled into one inlinable CSS bundle. Use when theming a report or deck, auditing contrast, or fixing dark-mode color drift.

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When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any "I need to actually understand X." Combines web search, URL fetch, agent-browser, last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on "/deep-research," "research X," "investigate X," "do a deep dive on X," "look into X," "what's actually happening with X," "due diligence on X," "validate this market." Differs from a one-shot web search: this is multi-pass with verification.

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Agentic eyes for Godot work: cross-platform screenshot CLI (asset/region/window/screen) to budgeted WebP, TEMP editor viewport bridge under .gdskills/, and Taste Receptor Atlas v2 (~237 micro-receptors × 0–2: hierarchy, contrast, typography×41, affordance, space, color, icon, composition, light/FX, motion-tells, anti-slop, originality, identity). Use when agents must see UI, assets, or the editor — not for in-game screenshot Autoloads. Keywords: agent vision, screenshot, WebP, visual QA, taste receptors, typography, UI review, asset sheet, editor viewport, anti-slop.

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Expert patterns for Godot 2D physics including collision layers/masks, Area2D triggers, raycasting, and PhysicsDirectSpaceState2D queries. Use when implementing collision detection, trigger zones, line-of-sight systems, or manual physics queries. Trigger keywords: CollisionShape2D, CollisionPolygon2D, collision_layer, collision_mask, set_collision_layer_value, set_collision_mask_value, Area2D, body_entered, body_exited, RayCast2D, force_raycast_update, PhysicsPointQueryParameters2D, PhysicsShapeQueryParameters2D, direct_space_state, move_and_collide, move_and_slide.

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Expert knowledge for Azure NetApp Files development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when deploying ANF for SAP HANA/Oracle, AVS datastores, AzAcSnap, cross-region replication, or object REST API, and other Azure NetApp Files related development tasks. Not for Azure Files (use azure-files), Azure Blob Storage (use azure-blob-storage), Azure Elastic SAN (use azure-elastic-san), Azure Managed Lustre (use azure-managed-lustre).

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Expert knowledge for Azure Container Storage development including troubleshooting, decision making, limits & quotas, security, and configuration. Use when configuring Elastic SAN-backed pools, CMK encryption, LRS/ZRS redundancy, volume resizing, or Prometheus/Grafana monitoring, and other Azure Container Storage related development tasks. Not for Azure Blob Storage (use azure-blob-storage), Azure Files (use azure-files), Azure Elastic SAN (use azure-elastic-san), Azure NetApp Files (use azure-netapp-files).

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Guides users through professional filmmaking workflows in Higgsfield Cinema Studio, including creating multi-shot sequences, configuring optical stacks, applying color grading, managing Soul Cast AI actors, and structuring per-scene prompts with Director Panel camera movements. Use when the user mentions Cinema Studio, Cinema Studio 2.5, Cinema Studio 3.0, Cinema Studio 3.5, Cinema Studio 4.0 (`cinematic_studio_video_4_0` — its four modes, camera/lens/aperture/era/genre/pacing ids, light presets, color palette), Soul Cast, color grading, multi-shot video, shot sequences, storyboard workflow, Hero Frame, optical stack, keyframe interpolation, Elements system (@Characters/@Locations/@Props), Speed Ramp, Director Panel, Higgsfield Popcorn, Single Shot / Multi-Shot Auto / Multi-Shot Manual modes, Reference Anchor, Smart shot control, or any professional filmmaking workflow inside Higgsfield.

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Reach into past AI conversation history through the `trellis mem` CLI. Use whenever the user asks 'how did we solve X last time', 'have we discussed this before', 'what was the decision on X', 'remind me what we did in this task', '上次怎么解的', '之前讨论过吗', '想起一段对话', or when starting a brainstorm that overlaps prior work, debugging a familiar bug, continuing a task across sessions, or doing a finish-work review. Returns raw past dialogue; decide for the moment whether to update spec, append to task notes, quote inline in the answer, or just internalize.

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Edit podcast audio or video — trim pre/post-show chat, remove filler words, cut silences, enhance audio quality, and cut a video version of the same edit. Use when the user asks to edit a podcast, clean up audio, remove fillers, trim a recording, or improve voice quality.

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Infrastructure as Code patterns (Terraform, Kubernetes), observability design (SLOs, metrics, alerting, dashboards), and pipeline security stages. Load when designing infrastructure, observability, or security scanning.

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Dung khi mot CA NHAN muon len hinh bang AI thay vi tu quay — pipeline avatar AI: 3 tier cong cu, 4 workflow gom avatar don, dich da ngon ngu, san xuat hang loat va hybrid nguoi that cong AI; nhan anh reference de tao prompt avatar; thay mat, style, logo; ghep voice clone; tranh bi nen tang danh dau; cong bo AI theo Nghi dinh 147/2024 va QA 100 diem. Cong cu HeyGen, Synthesia, ElevenLabs, Captions, Vbee. Kich hoat khi user nhac 'tao avatar AI', 'video HeyGen', 'talking head AI', 'lam video ma ngai lo mat', 'batch video AI', 'dich video sang tieng Anh', 'prompt avatar'. Khong dung cho — clone giong cho podcast va audio thi dung skill 25-voice-clone-podcast; viet loi thoai video thi dung skill 04-script-video; anh tinh thi dung skill 30-thiet-ke-master.

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Dung khi can TAO RA anh hoac prompt anh bang AI — anh thuong hieu ca nhan, logo, key visual campaign, anh dang hang ngay, editorial, infographic, mockup web, quote graphic. Tu doc brand identity trong context roi dung prompt, gen anh hoac xuat prompt cho MidJourney, DALL-E, Imagen, Leonardo. Co che do nhan anh reference va tra ve master prompt copy-paste duoc. Kich hoat khi user nhac 'thiet ke anh', 'lam logo', 've banner', 'prompt MidJourney', 'tao key visual', 'lam anh giong anh nay', 'gen anh AI', 'doi mau thuong hieu tren anh'. Khong dung cho — viet brief giao designer lam thi dung skill 42-brief-hinh-anh; quy trinh asset ca campaign thi dung skill 41-campaign-asset-list; video avatar AI thi dung skill 24-ai-avatar-production; UI wireframe tuong tac thi dung web-prototype; animation thi dung motion-frames.

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Zero-config goal-to-tasks engine (the Atlas engine). Takes any goal (software, pentest, business, learning), runs adaptive discovery via brainstorming, generates a validated spec, parses into TaskMaster tasks, and hands off to execution. Use when user says "PRD", "product requirements", "I want to build", invokes /atlas, or wants task-driven development.

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Phase 3 of the prd-taskmaster pipeline: smart mode selection and user handoff. Detects installed capabilities (superpowers, ralph-loop, task-master-ai, playwright, research providers), recommends ONE execution mode (A/B/C) with reasoned justification, appends the task-execution workflow to CLAUDE.md, surfaces a structured AskUserQuestion multi-option picker for user agency, and dispatches the chosen mode. Mode D (Atlas Fleet) is selectable only when detect_capabilities returns tier=premium (licensed atlas-launcher detected); otherwise it is a locked Atlas Pro teaser. Plan Mode is NOT used (spec section 13.5): AskUserQuestion is the sole user-agency mechanism. Declares HANDOFF complete so EXECUTE can follow.

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Execute the next TaskMaster task using the implementation plan with CDD verification. Picks the next ready task, matches it to the plan step, implements via a dispatched subagent, verifies subtasks with evidence, marks the task done, and loops until every task is complete. Wraps the TaskMaster next -> in-progress -> done lifecycle with CDD GREEN / RED / BLUE verification and the plugin's triple-verification rule. Autonomous by design — no user prompts inside the loop.

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Phase 0 of the prd-taskmaster pipeline. Resolves the active backend, initializes the project, configures the provider stack when the TaskMaster backend is active (DETECT-FIRST — never overwrite a working user config), and verifies the AI pipeline. Autonomous: zero user questions unless a hard block is hit. Declares the Setup phase complete so DISCOVER can follow.

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Expand all TaskMaster tasks with deep research before coding begins. Reads tasks.json, launches parallel research agents per task in waves using the research-expander agent. Writes findings back to tasks.json. Part of the prd-taskmaster toolkit. Use after PRD is parsed and before implementation. Invoke with /expand-tasks.

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Generate a Disaster Recovery plan with RTO/RPO targets. Use when someone asks to "create a DR plan", "disaster recovery", "business continuity", or "RTO RPO". Do NOT use for step-by-step restoration runbooks — use /pmstudio-recovery instead. Designed for SaaS platform products where Coco Inc is the customer — focuses on service continuity, data recovery, and vendor dependency management rather than infrastructure rebuild.

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Guides audio mastering for streaming platforms including loudness optimization and tonal balance. Use when the user has approved tracks and wants to master audio files.

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。