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Self-hosted semantic memory for AI agents via MCP. Save worklogs, decisions, and notes, then recall them across sessions by meaning, not keyword. Postgres + pgvector with auto-tagging.

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。

SurrealDB MCP for AI agents: built-in server (SurrealDB 3.1+ `surreal mcp`) and standalone surrealmcp (surrealdb/surrealmcp v0.4.0). Part of the surreal-skills collection.

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。

The only memory skill that watches on its own. No database. No vectors. No manual saves. Just an LLM observer that compresses your conversations into prioritised notes, consolidates when they grow, and recovers anything missed. Five layers of redundancy, zero maintenance. ~$0.00/month (using free-tier models). While other memory skills ask you to remember to remember, this one just pays attention.

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。

Brand voice, visual identity, messaging frameworks, asset management, brand consistency. Activate for branded content, tone of voice, marketing assets, brand compliance, style guides.

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A luxury-automotive brand whose marketing surfaces read as cinematic editorial. The base canvas is **near-black** (`#181818`) holding pure white display type; white-canvas bands appear only inside specific editorial contexts (preowned listings, pricing tables). The single brand voltage is **Rosso Corsa** (`#da291c`) — the iconic Ferrari racing red — used scarcely on primary CTAs, the Cavallino mark, and Formula 1 race-position highlights. Type runs **FerrariSans** at modest weights (display 500, body 400) — never bombastic. Spacing follows an explicit 8px token ladder (`xxxs` 4px through `super` 128px); generous editorial pacing throughout. The brand's strongest visual signature is the **full-bleed cinematic hero photograph** that fills the viewport top with car photography, model details, or trackside livery — followed by a tighter editorial body layout below.

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。

Maxim Brand Intelligence — brand identity, voice architecture, visual identity systems, messaging frameworks, brand consistency enforcement. Activate for brand strategy, brand audits, brand guidelines, tone of voice, asset compliance, color palette, typography specs. Powered by Maxim behavioral science layer.

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Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality

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Generates a step-by-step construction plan from a one-line objective, where each step is self-contained and executable by a fresh agent in a new session.

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Set up the Graphsignal Profiler for inference workloads — vLLM, SGLang, PyTorch, and dstack services. Use when the user wants GPU profiling, tracing, or monitoring for inference, asks about `graphsignal-run` or `graphsignal.watch()`, or asks about CUPTI / Prometheus / OTLP setup.

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。

Native agent-to-agent language for compact multi-agent messaging. A shared tongue agents speak directly, not a translation layer. 340+ atoms across 7 domains; 3x smaller than natural language.

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Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Keeps search noise on disk, hands the agent one path or block. Use for any audio, image, icon, logo, voiceover, caption, color-grading, or media-asset need.

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Create a comprehensive brand design guide — color palette, typography pairings, UI component previews, and visual identity rules with example mockups.

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。

Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.

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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.

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A terminal-native marketing system rendered entirely in Berkeley Mono — every word on the page, from the hero headline down to the footer fine print, is monospaced. The page itself reads like a manpage or a static-site README: warm cream canvas (`#fdfcfc`), nearly-black ink (`#201d1d`), 4px-radius rectangles for the few interactive elements, and bracketed `[+]`/`[-]` ASCII markers used as bullets. The brand's only "visual moment" is a single dark hero card that mocks up the OpenCode TUI itself — black background, monospaced terminal output, ASCII pipe characters, and a wordmark rendered as block-pixel ASCII. Every section sits as a hairline-bordered text block on the cream canvas with no shadows, no gradients, no decorative imagery, and no non-monospaced character anywhere in the system.

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MiniMax presents itself as a premium AI infrastructure brand through a striking duality — bold black-pill CTAs and stark white canvas for marketing, paired with vibrant gradient product cards (orange-red, magenta-pink, purple, blue) that turn each model release into a distinctive visual identity. The system uses DM Sans across all surfaces, employs an oversized 80px hero display, anchors major actions in deep near-black pills, and layers content density via a 3-column documentation grid with sidebar nav, prose body, and TOC. Coverage spans the marketing homepage, model showcase pages, developer documentation, and platform pricing surfaces.

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Comprehensive design skill: brand identity, design tokens, UI styling, logo generation (55 styles, Gemini AI), corporate identity program (50 deliverables, CIP mockups), HTML presentations (Chart.js), banner design (22 styles, social/ads/web/print), icon design (15 styles, SVG, Gemini 3.1 Pro), social photos (HTML→screenshot, multi-platform). Actions: design logo, create CIP, generate mockups, build slides, design banner, generate icon, create social photos, social media images, brand identity, design system. Platforms: Facebook, Twitter, LinkedIn, YouTube, Instagram, Pinterest, TikTok, Threads, Google Ads.

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。

Brand voice, visual identity, messaging frameworks, asset management, brand consistency. Activate for branded content, tone of voice, marketing assets, brand compliance, style guides.

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。