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Applies the reasoning of Stuart Russell, AI safety expert, UC Berkeley professor, and co-author of 'Artificial Intelligence: A Modern Approach'. Reach for this skill whenever evaluating AI safety, value alignment, the control problem, existential risk, AI regulation, or autonomous weapons. Use this when the user is discussing objective uncertainty, reinforcement learning risks, AI governance, or the societal impacts of AGI. Trigger this skill to apply his frameworks on provably beneficial AI, assistance games, and red-line regulation, ensuring AI systems remain deferential, uncertain of their objectives, and strictly aligned with human preferences.

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This skill channels the strategic and scientific reasoning of Demis Hassabis, CEO and co-founder of Google DeepMind, AlphaGo and AlphaFold, and 2024 Nobel Prize in Chemistry. Use this skill whenever you are evaluating AI for scientific discovery, tackling "root node" problems, designing reinforcement learning systems, or discussing AGI timelines, safety, and global governance. Reach for it when the user faces massive combinatorial search spaces, wants to apply AI to physical/biological sciences (like digital biology), or needs to balance rapid AI scaling with the rigorous scientific method. Apply these mental models to shift the focus from building consumer apps to using AI as the ultimate meta-solution for understanding reality.

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Applies the reasoning of David Silver, lead researcher on AlphaGo and AlphaZero at DeepMind, to problems of AI design, reinforcement learning, and open-ended discovery. Use this skill whenever you are designing AI systems, evaluating learning algorithms, balancing exploration vs. exploitation, choosing research problems, or discussing how to break past human performance ceilings. Reach for this whenever the user asks about self-play, Monte-Carlo Tree Search, tabula rasa learning, AGI, or moving from human-curated data to autonomous experience. It helps shift the focus from hardcoding human knowledge to building systems that learn for themselves.

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Applies the reasoning style of Ilya Sutskever (deep learning pioneer, co-founder of OpenAI and Safe Superintelligence Inc.) to problems involving AI architecture, scaling laws, alignment, and research strategy. Reach for this skill whenever discussing machine learning paradigms, the limits of compute and data, AGI timelines, superintelligence safety, or deciding between hardcoding vs. learning. Trigger this skill for questions about next-word prediction, reinforcement learning efficiency, generalization gaps, and transitioning from brute-force scaling to fundamental research, even if the user doesn't explicitly name him.

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Use this skill whenever you are reasoning about large-scale scientific projects, genomics, bioethics, data infrastructure, or long-term medical translation. Eric S. Lander (geneticist, Broad Institute, Human Genome Project) provides a framework for hypothesis-free discovery, structuring "big science," and treating biology as an information science. Reach for this when the user is discussing open science, collaborative ecosystems, CRISPR/gene editing ethics, managing massive datasets, or setting realistic timelines for technological breakthroughs. Apply his principles to avoid the "lone genius" myth, prevent overpromising, and build foundational infrastructure that serves the broader community.

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Plan pages, navigation and content sequence.

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Suede Labs skill that turns messy creator materials into a local, offline rights-and-provenance transfer package: inventoried and hashed assets, a normalized suede-intake.json manifest, credits and splits, license notes, provenance, and a missing-information report, validated by a bundled stdlib script. Use when a creator needs to hand a song, release, or project to a collaborator, advisor, registry, marketplace, or label; when someone asks for a rights package, intake package, or handoff folder; or when a validated manifest is needed before licensing or royalty-routing review. Carries questions, not answers: building the package clears nothing and uploads nothing. NOT FOR: finding or investigating the rights gaps in the first place (use suede-rights-audit); linting a release folder's files and metadata (use suede-release-linter); a sync one-sheet (use suede-sync-packaging).

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Suede-affiliated offer design for value framing, bonuses, guarantees, risk reversal, honest scarcity, naming, and payment structure. Use when the user is building or diagnosing a service, course, coaching, information-product, agency, or high-ticket B2B offer. NOT FOR: SaaS tier and value-metric architecture (use suede-pricing), sales-page copy (use suede-copy), or in-product upgrade prompts (use suede-paywalls).

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Define clear decision rights - Decider, Approver, Veto, Consulted, Informed. Use when clarifying who decides.

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Serverless Aura Graph Analytics (AGA) GDS Sessions — covers GdsSessions, AuraGraphDataScience, AuraAPICredentials, DbmsConnectionInfo, SessionMemory, get_or_create, remote graph projection with gds.graph.project.cypher and gds.graph.project.remote, gds.graph.project.native, gds.graph.construct, graphdatascience client 2.0 session endpoints, async compute and gds.jobs, AuraDB Cypher API memory/sessionId projection, algorithms, write-back, and session lifecycle. Use for AuraDB-connected, self-managed Neo4j, or standalone DataFrame/Spark session workloads. Does NOT cover the embedded GDS plugin on Aura Pro or self-managed Neo4j — use neo4j-gds-skill. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover Snowflake Graph Analytics — use neo4j-snowflake-graph-analytics-skill.

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Phase D of a WinForms-to-Avalonia migration: build the Avalonia UI shell with composition, MVVM state and commands, responsive XAML, accessibility, localization boundaries, and behavior-focused unit/Headless tests. Use only when an explicit migration is ready to port Forms or when the orchestrator routes here. Prefer this over control-by-control ports.

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Phase E of a WinForms-to-Avalonia migration: verify behavioral parity against Phase A contracts, record intentional differences, validate supported environments and packaging, and make evidence-based legacy cutover decisions. Use only for an explicit migration when comparing the legacy and Avalonia implementations or when the orchestrator routes here. Do not delete legacy without the cutover checklist and explicit authorization.

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Phase C of a WinForms-to-Avalonia migration: implement platform and infrastructure adapters for dependencies discovered in Phase A/B, such as persistence, process execution, dialogs, notifications, or environment capabilities. Use only in an explicit migration when such dependencies leak into Forms/core or when the orchestrator routes here. Do not invent adapters for capabilities the product does not have, and do not implement main-window XAML.

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Phase G of a WinForms-to-Avalonia migration: decompose oversized UI state and orchestration, harden asynchronous workflows and external boundaries, preserve composition lifetimes, keep Headless tests process-isolated, and update ownership documentation. Use only when an explicit migration has post-port structural or resilience debt, or when the orchestrator routes here. Baseline input security belongs in the phase that introduces the boundary, not only here.

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Persistent memory across AI sessions using ChromaDB vector database. Stores and retrieves context from past conversations, decisions, and code. Use when user asks to remember something, search past conversations, recall what was done before, save context for later, or find information from previous sessions. Do NOT use for git history or file-based notes.

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Sub-skill: Implement MPP Payment Discovery. Publish OpenAPI with x-payment-info extensions so AI agents discover payable endpoints via Machine Payment Protocol (mpp.dev).

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This skill should be used when the user asks to "use bilibili API", "download bilibili video", "get bilibili user info", "list bilibili favorites", "send bilibili danmaku", "upload video to bilibili", "monitor bilibili live room", "search bilibili", "get bilibili comments", or needs guidance on the bilibili_api Python library usage, authentication, API endpoints, or workflow patterns.

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Create professional investor pitch decks with structured content and visual design. Use when users need help with pitch deck, investor deck, fundraising deck, startup pitch, deck design, slide design, pitch presentation, pitch deck visuals, investor presentation, Series A deck, seed deck, or VC deck. Covers the full workflow: gathering company info, structuring narrative, generating a PowerPoint via script, and applying visual best practices.

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Unified skill for content strategy and marketing content strategy: content pillars, editorial calendars, keyword research by buyer stage, positioning, messaging hierarchy, trust-building, GEO/AI search optimization, and ROI measurement. Also handles content briefs, SEO briefs, content outlines for writers, on-page SEO optimization, meta descriptions, title tags, keyword density, content research, source discovery, expert sourcing, and information gathering. Use when planning content strategy, creating content briefs for writers, optimizing existing content for SEO, researching topics and sources, or managing editorial operations. Triggers: content strategy, marketing content strategy, content marketing strategy, content planning, editorial calendar, content pillars, messaging hierarchy, content brief, SEO brief, content outline, keyword research, buyer journey content, GEO optimization, AI search optimization, content ROI, content operations, content roadmap, brand messaging, positioning

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SEO, AEO (Answer Engine Optimization), and GEO strategy for search engines and AI visibility. Use when working on "SEO audit," "technical SEO," "on-page SEO," "AI search optimization," "AEO," "GEO," "AI visibility," "optimize for ChatGPT," "optimize for Perplexity," "AI Overviews," "answer engine optimization," "generative engine optimization," "AI citations," "featured snippets," "meta tags," "schema markup," "search ranking," "content optimization," "E-E-A-T," "structured data," "search console," "SEO health check," "why am I not ranking," "AI search readiness," "backlink strategy," "link building," "domain authority," "programmatic SEO," "SEO at scale," "template-based SEO," "AEO monitoring," "AI search monitoring," "JSON-LD," "rich snippets," "schema.org," "SERP analysis," "search intent," "site architecture," "information architecture," "URL structure," "internal linking," or "navigation." For keyword research, see keyword-research-and-clustering.

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Directly generate design-oriented AI images with strong creative direction and prompt engineering. Use this skill for posters, product visuals, PPT illustrations, infographics, teaching/demo diagrams, campaign key visuals, cover art, or when the user wants design-quality image generation rather than generic AI art. This skill turns a loose brief into a design brief, assembles a structured prompt, routes to the right Volcengine Seedream settings, and can generate the image immediately.

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Designs Amazon-compliant main product images and the 7 secondary image types (Infographic / Multi-angle / Detail Shot / Lifestyle / Variants / What's in Box / Size Reference) — with platform-mandatory main-image rules, conversion-rate-tuned secondary types per product category, and multi-image consistency anchored to the main image URL. Use when the user says "Amazon main image", "亚马逊主图", "product main image", "white background product image", "Amazon listing image", "亚马逊副图", "secondary images", "product carousel images", or any request for the 1:1 product image suite that lives on the Amazon detail page carousel. For A+ Content / detail-page modules (21:9 Hero Banner and 3:2 module layouts), see the `product-shots-detail-page` skill.

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Compact reference for the Hyperliquid API as the desk uses it - endpoints and envelopes, every /info request type, every /exchange action with its signing scheme, order and status vocabularies, asset ids, tick and lot rules, rate limits, WebSocket subscription list, error strings, and where the official docs are. Use to look up an exact field, request type or limit before writing a call, and to map an error string to its cause.

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Use when Antigravity should remember, recall, search, improve, or forget information using Cognee.

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。