「eth」の検索結果

Expert in designing and structuring online courses - curriculum architecture, learning outcomes, module design, and assessment strategies. Covers backward design methodology, scaffolding content, and creating courses that actually deliver transformation. Use when "create a course, course curriculum, course outline, learning outcomes, course structure, design a course, online course, " mentioned.

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Expert in Claude Code hooks - user-defined shell commands that execute at specific points in Claude Code's lifecycle. Provides guaranteed automation that doesn't rely on the LLM "remembering" to do something. Essential for enterprise workflows, code quality enforcement, and deterministic behavior in agentic coding. Use when "claude code hooks, automate claude, block tool use, pre tool use, post tool use, session start hook, claude lifecycle, claude-code, automation, hooks, lifecycle, cli, workflow, devtools" mentioned.

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The craft of creating and maintaining cohesive brand identity systems. Branding translates brand strategy into tangible visual and verbal identity—logos, color systems, typography, imagery, and voice guidelines that work together to make a brand recognizable and memorable. This skill covers logo design, visual identity systems, brand guidelines, naming, verbal identity, and brand application across touchpoints. Great branding is invisible when done right—it feels inevitable, as if the brand couldn't have looked any other way. Use when "logo, branding, brand identity, brand guidelines, visual identity, color palette, typography, brand book, naming, rebrand, brand refresh, brand system, branding, identity, logo, visual-design, guidelines, naming, typography, color" mentioned.

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Your most loyal users aren't just customers - they're potential advocates, contributors, and community members who can become the engine of your growth. Community-led growth isn't about broadcasting to an audience - it's about creating a space where your users connect with each other, share knowledge, and become invested in your success. This skill covers community strategy, platform selection, engagement tactics, ambassador programs, and the metrics that matter. Whether you're building a Discord for developers or a forum for power users, the goal is the same: creating genuine value that makes members want to stay and contribute. Use when "community, discord, forum, user group, ambassador, champions, developer relations, devrel, community engagement, community growth, power users, superfans, community, discord, engagement, devrel, ambassador, forum, user-community, growth, retention, champions" mentioned.

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Use when building DeFi protocols, implementing AMMs, yield farming strategies, or integrating with Ethereum/L2s - covers smart contract patterns, liquidity pools, and security considerationsUse when ", " mentioned.

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The orchestration layer for AI-native creative production. This skill coordinates multiple AI tools—video, image, audio, digital humans, effects—into cohesive campaigns, productions, and creative systems. As AI tools proliferate, the challenge shifts from "can we create this?" to "how do we orchestrate these capabilities into something coherent?" The AI Creative Director thinks in systems, not tools. In pipelines, not one-offs. In brand consistency across AI-generated assets. This is where creative vision meets technical orchestration. The AI Creative Director doesn't just use AI tools—they compose them into creative instruments that produce at scales and speeds previously impossible. Use when "AI creative director, orchestrate AI, AI campaign, multi-tool, AI workflow, AI pipeline, coordinate AI, AI production, AI creative system, full AI production, AI at scale, orchestration, creative-direction, ai-production, workflow, pipeline, multi-tool, scale, quality-control" mentioned.

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The science of learning through controlled experimentation. A/B testing isn't about picking winners—it's about building a culture of validated learning and reducing the cost of being wrong. This skill covers experiment design, statistical rigor, feature flagging, analysis, and building experimentation into product development. The best experimenters know that every test, positive or negative, teaches something valuable. Use when "a/b test, experiment, hypothesis, statistical significance, sample size, feature flag, variant, control, treatment, p-value, conversion rate, test winner, split test, experimentation, testing, statistics, feature-flags, hypothesis, growth, optimization, learning, validation" mentioned.

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Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragmented with inconsistent terminology. We use the CoALA cognitive architecture framework: semantic memory (facts), episodic memory (experiences), and procedural memory (how-to knowledge). Use when "agent memory, long-term memory, memory systems, remember across sessions, memory retrieval, episodic memory, semantic memory, vector store, rag, langmem, memgpt, conversation history, memory, vector-store, rag, retrieval, embedding, episodic, semantic, procedural, langmem, memgpt, pinecone, qdrant, chromadb" mentioned.

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Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when "keywords, file_patterns, code_patterns, " mentioned.

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Accessibility isn't a feature - it's a fundamental quality of good software. 1 in 4 adults has a disability. Many more have temporary impairments or situational limitations. Your users include people who can't see, can't hear, can't use a mouse, or can't process information the way you do. This skill covers WCAG guidelines, ARIA patterns, keyboard navigation, screen reader compatibility, and automated testing. Key insight: accessible code is better code. The constraints of accessibility lead to simpler, more semantic, more maintainable implementations. 2025 lesson: Accessibility lawsuits are at an all-time high. "We'll add it later" is both ethically wrong and legally risky. Start accessible, stay accessible. Use when "accessibility, a11y, wcag, aria, screen reader, keyboard navigation, focus trap, alt text, color contrast, skip link, accessible, accessibility, a11y, wcag, aria, screen-reader, keyboard, inclusive, semantic-html" mentioned.

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The new frontier of audio: AI-generated music with Suno and Udio, AI sound effects with ElevenLabs, AI voice cloning, and AI audio enhancement. This skill covers the full spectrum of neural audio synthesis and manipulation. We're in an era where a single person can produce broadcast-quality audio content that would have required studios, musicians, and engineers. AI doesn't replace musical talent—it democratizes production capability. Original compositions in minutes. Custom sound design in seconds. Voice in any language instantly. The practitioners of this skill understand both the creative potential and the ethical considerations. They know when AI audio enhances creativity and when it needs human touch. They're audio directors who orchestrate AI tools like instruments in a symphony. Use when "AI music, generate music, Suno, Udio, AI audio, AI sound, generate soundtrack, background music, sound effects, audio generation, jingle, AI score, stem separation, ai-audio, music, suno, udio, sound-effects, soundtrack, generation, audio-branding, production" mentioned.

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Audit whether a paper's baseline comparisons are COMPLETE, FAIR, and SIGNIFICANT: a required recent SOTA baseline is missing while 'best/SOTA' is claimed (HP-MISSING-BASELINE); a baseline is undertuned / given less compute-tuning-data, run at a mismatched config, or the equal-budget ablation-as-baseline is absent (HP-WEAK-BASELINE); 'outperforms' is asserted over overlapping error bars or with no variance/seeds (HP-SIG-OVERLAP); and a cross-row 'improves over baseline by X%' is arithmetically wrong (HP-DELTA-ERROR, cross-row form only). A versioned per-domain baseline profile + a live leaderboard/recency search are assembled by the EXECUTOR as structured facts; a fresh cross-model reviewer (gpt-5.6-sol xhigh, read-only, fresh thread per dimension) PROPOSES findings, each span-anchored to a ledger claim_id; tools/adjudicate_findings.py DECIDES the verdict. Works at L0 (stated comparisons) and deepens at L2 (configs/result files). A completeness question it cannot settle internally becomes needs_external_check, never a guessed missing baseline. Emits baseline-comparison-audit.findings.json; computes NO verdict. Detect-only. Triggers: "baseline audit", "missing baselines", "is the comparison fair", "weak baseline", "baseline 误报", "SOTA earned?".

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Challenges a recommendation, design, large change, or any artifact submitted for hard review (spec, proposal, policy, plan) across 5 dimensions (consistency, completeness, actionability, alignment, risk), from the standards of a named senior expert in the artifact's domain and ideally from a fresh context or a different model. Searches assuming defects exist and reports only those that survive evidence. Panel mode runs several independent lenses in parallel on a release candidate, verifies every finding against the current head, and routes confirmed ones to file owners. Use before shipping a significant recommendation, design, large branch, or multi-agent release, or when asked to tear something apart, be brutally honest, or poke holes in it.

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摄影 (摄影 (Photography) — 以静态影像为产出的视觉创作 + 服务行业：从看见 → 用光 → 构图 → 拍摄 → 后期 → 交付的认知操作系统，覆盖商业摄影 (commercial: 产品/广告/电商/美食)、人像摄影 (portrait: 影楼/写真/婚礼/时尚/环境人像)、纪实与街头摄影 (documentary/photojournalism/street)，以及与之贯通的风光、新闻、艺术摄影。面向职业摄影师 / 助理 / 修图师 / 想转职业的资深爱好者 / 服务这行的人 (器材厂商、图库、后期外包、影楼运营)。覆盖: (a) 第一性张力 — **光 (light is the craft — 看光、控光、塑光：硬光/柔光、方向、色温、光比、布光是摄影第一性) ⇄ 器材 (gear — 相机/镜头/灯具迷信, 'GAS' gear-acquisition-syndrome, 'the best camera is the one you have with you' — 器材不是摄影)**; **决定性瞬间/抓取 (decisive moment, Cartier-Bresson, 等待与预判, 纪实/街头不可重来) ⇄ 构建/导演 (constructed/directed, 商业与人像是布光摆姿造光的'制造'而非'捕获')**; **前期/拍对 (get it right in camera, 曝光/白平衡/构图当场拍对) ⇄ 后期/暗房 (post/darkroom, Ansel Adams 'negative is the score, print is the performance' — RAW 冲洗/调色/修图是创作一半)**; **作者性/艺术表达 (vision, personal voice, 'photograph what you feel not what you see') ⇄ 服务性/商业交付 (client brief, 影楼标准化出片, 'shoot the brief not your ego', 摄影是生意)**; **真实/未操纵 (truth, photojournalism ethics, 不过度 PS, 新闻摄影伦理) ⇄ 修饰/理想化 (retouch, 商业人像液化磨皮, 广告的'谎言')**; **决定性技术参数 (曝光三角 aperture/shutter/ISO, 景深, 互易律) ⇄ 看见/眼力 (seeing, 'photography is about seeing not cameras', 构图/光感是 tacit 眼力)**; **胶片/慢/不可见 (film, 慢工, 不可即时回看, 暗房) ⇄ 数码/即时/海量 (digital, chimping, 连拍, 后期无限)**; AI 对摄影的冲击 ('是不是摄影'、生成式填充/换天/AI 修图、真实性危机); (b) 核心工作流 / pipeline (最标准、最易蒸高质量+CLI 化) — 通用链: 看光选光 → 曝光三角决策 (光圈定景深/快门定动静/ISO 兜底) → 测光与曝光 (评价/点测光, 向右曝光 ETTR, 直方图, 区域系统) → 构图 (三分法/引导线/框架/负空间/前景) → 对焦 → 拍摄 → 选片 culling → RAW 后期 (Lightroom/Capture One: 曝光/白平衡/色调曲线/HSL/局部) → 精修 retouch (Photoshop: 频率分离/液化/D&B) → 调色 grading → 输出交付 (色彩管理/sRGB/打印/图库上传); 子流派 SOP: 影棚商业布光 (主光/辅光/轮廓光/背景光, 三点布光, 光质修饰器 softbox/beauty-dish/grid)、婚礼/纪实一天流程、街头扫街、产品/电商台面、人像引导摆姿 posing & direction; (c) 工具栈 — 相机系统 (无反主导: Sony A 系 / Canon R / Nikon Z / 富士 X&GFX / 徕卡 M; 中画幅 Phase One/Hasselblad/GFX 商业; 残幅 vs 全幅 vs 中幅)、镜头 (大三元, 定焦 vs 变焦, 35/50/85 人像三剑客, 微距, 移轴)、灯具 (机顶闪 Godox/Profoto, 影室灯, 常亮 LED, 持续光 vs 闪光)、修饰器 (柔光箱/反光伞/束光筒/雷达罩/旗板)、测光/附件 (测光表, 灰卡, 三脚架, 滤镜 ND/CPL/渐变)、后期软件 (Adobe Lightroom Classic/CC 主导, Capture One 商业/影室, Photoshop 精修, DxO PhotoLab/PureRAW 降噪, Capture One vs Lightroom 之争, 国产: 醒图/泼辣 Polarr/Snapseed 移动端, RawTherapee/Darktable 开源, AI: Lightroom 生成式/Photoshop Generative Fill/Topaz Photo AI/Gigapixel/Luminar Neo)、色彩管理 (X-Rite/Calibrite 校色仪, ICC, 显示器)、图库/交付 (Pixieset/图虫/500px/视觉中国/Getty/Adobe Stock, 客片在线选片); (d) 知识正典 — Ansel Adams 'The Camera / The Negative / The Print' 三部曲 + 区域系统 (Zone System)、Henri Cartier-Bresson 'The Decisive Moment'、Michael Freeman 'The Photographer's Eye' (构图) 'The Photographer's Mind'、Bryan Peterson 'Understanding Exposure' (曝光入门圣经)、Scott Kelby 'Digital Photography Book' 系列 + Lightroom/Photoshop 书、Joe McNally 'The Hot Shoe Diaries / Sketching Light' (闪光灯)、Light Science & Magic (布光科学经典教材)、Roland Barthes 'Camera Lucida' (摄影哲学)、Susan Sontag 'On Photography'、John Szarkowski 'The Photographer's Eye'、National Geographic 摄影指南、Robert Capa / Sebastião Salgado / Steve McCurry (纪实)、Annie Leibovitz / Richard Avedon / Peter Lindbergh (人像/时尚)、Galen Rowell / Ansel Adams (风光); (e) figures/流派 — 风光/系统派 (Ansel Adams 区域系统奠基、Galen Rowell 探险风光、Marc Adamus); 决定性瞬间/纪实街头派 (Henri Cartier-Bresson 奠基、Robert Capa 战地、Sebastião Salgado 社会纪实、Steve McCurry、Vivian Maier、Daido Moriyama、森山大道/荒木经惟 日本派、Vivian Maier); 人像/时尚派 (Richard Avedon、Annie Leibovitz、Peter Lindbergh、Platon、Joey L、Lindsay Adler 时尚布光); 布光/教育派 (Joe McNally、Zack Arias 'one light'、Profoto/strobist David Hobby 'Strobist' 闪光灯启蒙博客、Karl Taylor 商业布光教学); 商业/广告派 (Chase Jarvis 'CreativeLive'创办+'best camera'、Joel Grimes、Tim Wallace 汽车); 后期/修图派 (Pratik Naik、Aaron Nace 'Phlearn'); 街头当代派 (Eric Kim 街头博客、Joel Meyerowitz、Saul Leiter 色彩街头); 中文圈 (李涛 'photoshop教学'、宁思潇潇 器材评测、thomas 'Thomas看看世界' 风光后期、阿刘 风光、668 人像); 哲学/批评 (Susan Sontag、Roland Barthes、John Szarkowski MoMA); (f) 行业话术/黑话 — 曝光三角 exposure triangle / 光圈 aperture f-stop / 快门 shutter speed / 感光度 ISO / 景深 DoF depth of field / 焦段 focal length / 等效 / 全画幅 full-frame vs 残幅 crop / 大三元 / 定焦 prime / 互易律 reciprocity / 向右曝光 ETTR / 直方图 histogram / 高光溢出 clipping / 动态范围 dynamic range / 宽容度 / 白平衡 WB

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GitHub 解封 — 账号封禁/限制/恢复的领域操作系统。覆盖：(a) GitHub 官方政策体系 (TOS / 可接受使用政策 / Trust & Safety 执行模式 / 公开申诉路径 / 受制裁地区解读)；(b) 封号原因诊断学 (spam / abuse / 制裁误标 / 2FA 丢失 / ToS 违规 / 账号劫持误判 / ban evasion 等子类型 + 症状→原因映射 + 自我分诊压测)；(c) 申诉实操 craft (写一封能让 T&S 快速判误伤的英文申诉信 + 升级阶梯 + 法务介入边界 + Don'ts)；(d) 制裁与合规硬边界 (OFAC SDN 名单 / 哪些国家或地区真不可达 / VPN 误判路径 / 中国大陆不是美国制裁地区的反复重申)；(e) 中国大陆开发者特别处境 (sanctioned region 误标 + SMS 验证不支持 +86/+852 + Gitee/GitLab/Codeberg/JihuLab 备用迁移 + 私有自托管 Gitea/Forgejo)；(f) 真实案例库 (~30+ 公开案例分类拆解：误伤 / 真违规 / 制裁误标三类各自赔率与申诉成功路径)。伦理锚绝不软化：不教 ban evasion / 不教撒谎式申诉 / 真违规承认改进 / 丢 2FA 无恢复因子则诚实告知 / 中国制裁误标靠申诉不靠换 VPN / 申诉 6 个月窗口必算清 / 约 3% (业内估) 真违规恢复 vs 约 79% (业内估) 误伤申诉成功率分层标。 (GitHub Account Reinstatement — the domain operating system for GitHub (and analogous platform) account suspension, restriction, appeal, and recovery. Covers: (a) GitHub official policy architecture (TOS / Acceptable Use Policies / Trust & Safety enforcement patterns / public appeals pathways / sanctioned-region interpretation); (b) suspension-cause diagnostics (spam / abuse / sanctions mis-flag / 2FA loss / ToS violation / account hijack false-positive / ban evasion taxonomy + symptom→cause mapping + self-triage pressure test); (c) appeal craft (writing an English appeal letter that gets T&S to fast-track a false-positive ruling + escalation ladder + legal-engagement boundary + Don'ts); (d) sanctions and compliance hard boundaries (OFAC SDN list / which countries/regions are truly unreachable / VPN false-positive paths / China is NOT a US-sanctioned region — repeated emphasis); (e) mainland China developer special circumstances (sanctioned-region mis-flag + SMS verification does not support +86/+852 + Gitee/GitLab/Codeberg/JihuLab fallback migration + self-hosted Gitea/Forgejo); (f) real-case library (~30+ public cases with categorized analysis: false-positive / genuine violation / sanctions mis-flag, each with win-rate and appeal success path). Ethical anchors absolutely not softened: do NOT teach ban evasion (creating new accounts turns a temp ban into a permanent one — the single biggest mistake); do NOT teach social engineering or lying in appeals (misuse + actually confirms violation); genuine violations: admit + improve beats denial; lost 2FA + no recovery factor → do not pretend recovery is possible; China sanctioned-region mis-flag → fix via appeal, not repeated VPN switching; appeal form 6-month window must be counted carefully; historical 约 3% (业内估) genuine-violation recovery vs 约 79% (业内估) false-positive appeal success rate stratification must be honestly labeled. Anti-samples (explicitly describe harm, never endorse): developer permabanned for ban evasion / open-source team org-banned for personal attacks in public issues / cases where repeated VPN switching escalated risk-control severity.) Master OS — automated mastery of GitHub Account Reinstatement — the domain operating system for GitHub (and analogous platform) account suspension, restriction, appeal, and recovery. Covers: (a) GitHub official policy architecture (TOS / Acceptable Use Policies / Trust & Safety enforcement patterns / public appeals pathways / sanctioned-region interpretation); (b) suspension-cause diagnostics (spam / abuse / sanctions mis-flag / 2FA loss / ToS violation / account hijack false-positive / ban evasion taxonomy + symptom→cause mapping + self-triage pressure test); (c) appeal craft (writing an English appeal letter that gets T&S to fast-track a false-positive ruling + escalation ladder + legal-engagement boundary + Don'ts); (d) sanctions and compliance hard boundaries (OFAC SDN list / which countries/regions are truly unreachable / VPN false-positive paths / China is NOT a US-sanctioned region — repeated emphasis); (e) mainland China developer special circumstances (sanctioned-region mis-flag + SMS verification does not support +86/+852 + Gitee/GitLab/Codeberg/JihuLab fallback migration + self-hosted Gitea/Forgejo); (f) real-case library (~30+ public cases with categorized analysis: fa

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Use when the user is debugging a bug, tracing an error, or asking why something fails. Examples: "Why is X failing?", "Where does this error come from?", "Trace this bug"

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Use when the user wants to know what will break if they change something, or needs safety analysis before editing code. Examples: "Is it safe to change X?", "What depends on this?", "What will break?"

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Routes, triages, flags and rates a piece of text with a probability for every option: which department or queue a ticket goes to, which intent a message expresses, whether a yes/no condition holds (is this tool call grounded, should the agent ask first, is the customer angry), and how severe or urgent it is on a rubric, each with a calibrated confidence. Runs Claude Haiku in the request and response shapes of OpenAI's Decisions API, for when no purpose-built decision model is at hand. Use for "route this ticket", "triage these", "classify with a confidence", "give me a probability that", "rate the severity", "score against this rubric", guardrail checks before a tool call, or "a Decisions API without OpenAI".

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Systematic research methodology for building comprehensive, current knowledge on any topic. Requires web_search tool. Use when questions require thorough investigation, recent developments post-cutoff, synthesis across multiple sources, or when Claude's knowledge may be outdated or incomplete. Triggered by "Research", "Investigate", "What's current on", "Latest info on", complex queries needing validation, or technical topics with recent changes.

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Analyzes an AI/ML publication — paper, preprint, article, technical blog post — and extracts what an enterprise AI engineer should do about it. Use when someone supplies a URL or document on RAG, embeddings, fine-tuning, prompt engineering, agents, or LLM deployment and asks "review this paper", "what do you make of this", "is this worth adopting", or "summarise the method and its limits". The subject matter must itself be machine learning.

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Multi-conversation methodology for iterative stateful work with context accumulation. Use when users request work that spans multiple sessions (research, debugging, refactoring, feature development), need to build on past progress, explicitly mention iterative work, work logs, project knowledge, or cross-conversation learning.

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Interpret video content visually by sampling frames into timestamped contact sheets that can be read as images. Use when: user asks what happens in a video; asks to summarize, describe, review, or QA video content or footage; asks about scenes, actions, people, or objects in a video; needs a storyboard-style overview of a clip; asks to find where something occurs in a video. Triggers on 'watch this video', 'what's in this video', 'summarize the video', 'describe the footage', 'contact sheet', 'storyboard', 'review this clip', 'find the scene where', 'scene detection', 'shot boundaries', 'detect cuts', 'dwell points'. For converting, trimming, or transcoding video, use processing-video instead.

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Listen to generated music by measuring it and by reading it as sheet music: render Strudel code or record a Web Audio page through the real engine in headless Chromium, then read spectrograms, pYIN pitch lines, chroma, roughness and semitone-rub meters; engrave notes as a score with beat-by-beat harmony; transcribe a melody from audio; read MusicXML/MIDI/ABC or a score image into notes and into Strudel code. Use to check whether generated music sounds right or better (before/after a change), to match a reference track, spectrogram image or score, or to find discordant chords, a buried melody, clipping or muddy mixes. Triggers on 'does it sound better', 'listen to', 'render and check', 'spectrogram', 'sfft/stft', 'discordant', 'clashing chords', 'sounds off', 'compare to the original', 'reproduce this track in Strudel', 'sheet music', 'score', 'notation', 'MusicXML', 'MIDI', 'ABC', 'transcribe', 'OMR'. Pairs with strudeling (writing Strudel); for format conversion use processing-video.

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Exhaustive problem space exploration using the MIT Synthetic Neurobiology "tiling tree" method. Partitions a problem into MECE (Mutually Exclusive, Collectively Exhaustive) subsets recursively via parallel subagents, then evaluates leaf ideas against specified criteria. Use when users say "tiling tree", "tile the solution space", "exhaustively explore approaches to", "what are all the ways to", or request a MECE breakdown of a problem. Requires orchestrating-chat-agents skill.

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