规划、编写、审阅和修复由真实授权素材与 AI 生成镜头混合制作的电影级文旅宣传片。用于文旅短片创意简报、场景图筛选、首帧空间分析、分镜脚本、画面内容提示词、人物动作、导演级运镜、自然动机布光、转场与尾帧衔接、Seedance 2.0/可灵/Midjourney 提示词、生成结果诊断、时间线与合规风险检查;尤其适用于需要写实、辽阔、自由感和角色剧情连续性的项目。
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。
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规划、编写、审阅和修复由真实授权素材与 AI 生成镜头混合制作的电影级文旅宣传片。用于文旅短片创意简报、场景图筛选、首帧空间分析、分镜脚本、画面内容提示词、人物动作、导演级运镜、自然动机布光、转场与尾帧衔接、Seedance 2.0/可灵/Midjourney 提示词、生成结果诊断、时间线与合规风险检查;尤其适用于需要写实、辽阔、自由感和角色剧情连续性的项目。
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。
Install the PRD-Driven Context Engineering methodology into a fresh OR existing repository — the subscription-native alternative to forking the whole repo. Runs an interactive wizard that seeds the framework (.claude/ hooks, skills, agents, rules, scripts) without clobbering product content. Triggers on "install the methodology", "adopt this into my repo", "self-install", "set up PRD lifecycle here", "onboard existing project". Outputs an installed framework + a verification report.
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。
Decision framework for isolating every external dependency in a test suite: when to use in-process mocks, HTTP stubs (MSW, WireMock), record-replay, fault injection (Toxiproxy), or ephemeral real services (Testcontainers), and how to enforce that no real calls escape in CI. Use when: "mock service," "stub API," "fake service," "WireMock," "MSW," "Toxiproxy," "test isolation," "dependency management," "stub an external API in CI." Not for: consumer-driven contract verification (Pact, broker) — use contract-testing; standing up a full Docker Compose env or seed data — use test-environments; broad resilience/game-day fault campaigns — use chaos-engineering. Related: contract-testing, test-environments, api-testing, test-data-management, chaos-engineering.
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。
Design environment strategy for testing across dev, CI, preview, staging, and production — Docker Compose test infrastructure, multi-stage Dockerfiles, seed-data lifecycle, per-PR preview environments, production parity, and external-dependency stubbing at the HTTP boundary. Use when: "set up test environment," "docker-compose for tests," "per-PR preview environment," "staging parity," "spin up test infra," "environment tiers." Not for: choosing mock-vs-stub-vs-fake per dependency — use service-virtualization; factory and fixture data patterns — use test-data-management; pipeline/Actions config — use ci-cd-integration. Related: test-data-management, ci-cd-integration, contract-testing, service-virtualization.
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。
Goal-driven E2E testing where a browser agent (Playwright MCP / computer-use) reads a natural-language goal and explores the app via the accessibility tree to assert outcomes — no pre-written script. Covers when intent-driven beats scripted, making agent runs deterministic (pinned model, temperature 0, seeded data, bounded steps, explicit success assertion, snapshot-not-pixel), cost/latency control, the accessibility-tree-first interaction model, CI gating, and graduating a stable run into a scripted Playwright test. Use when: "agentic browser test," "goal-driven browser test," "let an agent explore the app," "natural-language E2E," "browser agent smoke test," "Playwright MCP test." Not for: Writing/maintaining deterministic scripted Playwright tests — that is playwright-automation. Testing your product's OWN LLM features — that is ai-system-testing. Related: playwright-automation, ai-system-testing, exploratory-testing, test-reliability, qa-project-context.
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。
Turn a vague bug report into a VERIFIED minimal reproduction and then a failing regression test, agent-driven end to end. Covers extracting the implicit repro from a thin report (env, build, steps, data), the reproduce-minimize-isolate-capture loop, git bisect to find the introducing commit, building a deterministic minimal repro (fixed seeds, frozen time, stubbed network), writing the failing regression test BEFORE the fix (red) and confirming the fix flips it green, and writing repro evidence back into the ticket. Distinguishes flaky-not-reproducible from environment-specific. Use when: "reproduce this bug," "minimal reproduction," "repro steps," "find the commit that broke it," "git bisect," "make the repro deterministic," "write a failing test for this bug," "regression test for a defect," "can't reproduce this bug." Not for: Classifying/deduplicating/severity-routing existing failures without reproducing them — that is ai-bug-triage. Generating tests from specs rather than from a defect — that is ai-test-generation. Related: ai-bug-triage, ai-test-generation, test-reliability, systematic-debugging, qa-project-context.
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。
Generates fuzz test scaffolding for parsers handling external input (YAML, JSON, config files, user input). Seeds corpus from existing fixtures and runs initial pass. Use when implementing or changing a parser, or any code that ingests user input, webhook payloads, API responses, or file formats.
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。
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?".
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。
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
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。
加密链上交易 (加密 / 链上交易 (Crypto & On-chain Trading) — 以加密资产为标的、强调链上活动的主动交易认知操作系统:从「看叙事/选赛道 → 找标的 → 链上尽调与风控 → 选场所(DEX/CEX/链上合约) → 建仓与仓位管理 → 监控链上流向与情绪 → 退出与复盘」的完整决策链。覆盖 (a) 第一性张力 — **链上 on-chain (DEX 现货/AMM、钱包追踪 wallet tracking、资金流向 flow、MEV、memecoin、链上衍生品 Hyperliquid/GMX、自托管 self-custody, 'not your keys not your coins') ⇄ 链下 CEX (中心化交易所现货/合约 Binance/OKX/Bybit、订单簿、托管、出入金法币)**; **合约/杠杆/衍生品 (perps 永续、资金费率 funding、清算 liquidation、爆仓、做多做空、高频/择时) ⇄ 现货/价值/长持 (spot、HODL、定投 DCA、基本面/估值、'time in market > timing the market')**; **价值/基本面派 (协议收入、TVL、代币经济学 tokenomics、真实使用、估值模型) ⇄ meme/叙事/情绪派 (memecoin、narrative rotation 叙事轮动、attention is the asset、纯博弈/PvP、Ponzinomics)**; **链上数据/量化/客观 (on-chain analytics, Nansen/Arkham/Dune、聪明钱 smart money、链上指标、系统化/机械化) ⇄ 直觉/盘感/叙事阅读 (narrative、KOL alpha、社群情绪、tape reading)**; **自托管/去中心化/抗审查 (DeFi、自托管钱包、抗审查、'be your own bank') ⇄ 便利/合规/中心化 (CEX、合规出入金、KYC、托管、ETF)**; **主动交易/择时/高换手 (trading、波段、合约、撸毛/空投 airdrop farming、套利 arbitrage) ⇄ 被动配置/低换手 (配置 BTC/ETH、ETF、长期叙事 beta)**; (b) 核心工作流 / pipeline (最标准、最易蒸高质量 + CLI 化) — 通用链: 叙事/赛道判断 (宏观周期/减半/流动性/板块轮动) → 标的发现 (链上扫链/聪明钱跟单/新币/叙事映射) → 尽调 due diligence (代币经济学/解锁 unlock/团队/合约审计/honeypot 检测/流动性与持仓分布) → 风控前置 (仓位 sizing/最大回撤/止损/相关性) → 场所与执行 (CEX vs DEX、滑点/MEV/gas、限价 vs 市价、TWAP) → 持仓监控 (链上流向/巨鲸/资金费率/解锁日历/情绪指标) → 退出与复盘 (止盈分批/再平衡/记录交易日志); 子流派 SOP: 链上 degen 打新与 memecoin 流程、合约交易者的资金费率与清算地图、空投/撸毛 farming、套利与 MEV、被动配置与定投; (c) 工具栈 — 链上分析 (Nansen 聪明钱/Arkham 实体标注/Dune 自建仪表盘/Dexscreener & DEX Screener 新币/GMGN & Photon & BullX memecoin 终端/Etherscan & Solscan 区块浏览器/DeBank 钱包总览/Token Terminal 协议基本面/DefiLlama TVL/Glassnode & CryptoQuant 链上指标)、交易场所 (CEX: Binance/OKX/Bybit/Coinbase; 链上现货 DEX: Uniswap/Jupiter/Raydium/Aerodrome; 链上衍生品: Hyperliquid/GMX/dYdX)、钱包与安全 (MetaMask/Rabby/Phantom 热钱包、Ledger/Trezor 硬件冷钱包、Revoke.cash 授权管理、honeypot/合约扫描)、行情与图表 (TradingView、CoinGecko/CoinMarketCap)、信息与聚合 (Twitter/X、Telegram、DeFiLlama、RootData/ICO 日历、解锁日历 Token Unlocks)、自动化 (交易机器人、链上 bot/sniper、Telegram trading bot); (d) 知识正典 — 注意加密交易 canon 偏少且新: 通用交易/风控经典 (Edwin Lefèvre 'Reminiscences of a Stock Operator'、Van Tharp 'Trade Your Way to Financial Freedom' 仓位管理、Mark Douglas 'Trading in the Zone' 交易心理、Michael Mauboussin、Nassim Taleb 'Fooled by Randomness/Antifragile')、加密原生 (Bitcoin whitepaper 中本聪、'The Bitcoin Standard' Saifedean、Vitalik 博客与 Ethereum whitepaper、'DeFi and the Future of Finance'、Lyn Alden 宏观、a16z crypto 文章、Messari/Delphi/Bankless 研报)、链上分析方法 (Glassnode/CryptoQuant 教程、Nansen/Arkham/Dune 文档、Dune Analytics SQL)、交易方法论散见于 podcast/Substack/Twitter thread 而非书; (e) figures/流派 — 价值/基本面派 (Vitalik Buterin 以太坊、Hasu/Su Zhu(争议)、Arthur Hayes BitMEX 创始人/宏观+衍生品、Raoul Pal、Lyn Alden 宏观、Cobie/Jordan Fish UpOnly podcast、DeFi 研究 Bankless Ryan Adams/David Hoffman); 链上分析派 (Nansen Alex Svanevik、Arkham、Adam Cochran、Ansem(blknoiz06) 链上交易、Murad memecoin supercycle、链上侦探 ZachXBT 反诈); 合约/衍生品派 (Arthur Hayes、GCR(GiganticRebirth) 传奇合约、Pentoshi、CryptoCred 技术分析、Tyler Durden); meme/叙事派 (Ansem、Murad、Cobie、各 Solana memecoin KOL); 宏观/周期派 (Raoul Pal、Lyn Alden、PlanB stock-to-flow(争议)、Benjamin Cowen 数据/周期); 量化/系统化 (各匿名量化、Hyperliquid 生态); 中文圈 (链上分析/合约 KOL、币圈大 V、播客如 '无人之境'/'Web3 佛学院'、研究机构如 Foresight/PANews/律动 BlockBeats); 反诈/安全 (ZachXBT、SlowMist 慢雾、go+ 安全); (f) 行业话术/黑话 — 现货 spot / 合约 perps 永续 / 杠杆 leverage / 多空 long-short / 爆仓 liquidation 清算 / 资金费率 funding rate / 开多开空 / 止损 SL 止盈 TP / 仓位 position sizing / 满仓梭哈 ape in / 梭 / FOMO / FUD / 钻石手 diamond hands / 纸手 paper hands / 韭菜 / 镰刀 / 庄 / 出货 / 拉盘砸盘 / 插针 wick / 针 / 上车下车 / 埋伏 / 潜伏 / 链上 on-chain / 钱包 wallet / 地址 / 聪明钱 smart money / 巨鲸 whale / 跟单 copy-trade / 老鼠仓 / 貔貅盘 honeypot / 貔貅 / rug 跑路 rug-pull / 归零 / 土狗 (memecoin/小币) / 金狗 (暴涨百倍) / meme 币 / 叙事 narrative / 赛道 / 板块轮动 / 撸毛 撸空投 airdrop / 女巫 sybil / 交互 / 解锁 unlock / 砸盘解锁 / 代币经济学 tomomics / TVL / APY APR / 无常损失 IL / 滑点 slippage / MEV / 三明治 sandwich / gas / 抢跑 frontrun / 貔貅检测 / 授权 approve / 撤销授权 revoke / 私钥 助记词 seed phrase / 冷钱包 热钱包 / 自托管 / 减半 halving / 牛熊 / 山寨季 altseason / 比特币市占率 BTC.D / 山寨 alt / 主流币 / DeFi 暑期 / GM / WAGMI / NGMI / 归零归零 / PvP / Ponzi 庞氏; (g) 争议/批
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。
AIGC 创作工作流 (AIGC 创作工作流 / AIGC Creative Workflow — 以「生成式 AI 视觉创作(图像 + 视频)的工程化创作流水线」为对象的认知操作系统:从「需求/概念(要做什么画面/镜头/风格)→ 模型与工具选型(Midjourney / Stable Diffusion·SDXL·Flux / ComfyUI / 可灵 Kling / 即梦 Jimeng / Runway / Vidu / Sora)→ Prompt 与参数设计(提示词工程、风格描述、负向、种子、CFG/步数/采样器、参考图)→ 可控生成(ControlNet / LoRA / IPAdapter / inpainting / 图生图 / 局部重绘 / 区域控制)→ 批量出图与筛选 → 精修与合成(放大/超分、修手修脸、PS/AE 后期、抠图合成)→ 图生视频/文生视频(首尾帧、运镜、时长、一致性、对口型)→ 商业交付与迭代复现(参数留存、工作流文件复用、版权与可商用判断)」的完整创作-工程-交付决策链。覆盖 (a) 第一性张力 — **可控性/工程化复现(ControlNet/LoRA/ComfyUI 节点工作流/固定种子与参数/可复现可迭代)⇄ 随机性/抽卡玄学(出图随机、prompt 玄学、抽卡刷图、靠运气)**;**审美/创意/艺术指导主导(人的审美判断、概念设计、构图、镜头语言、艺术总监能力——'模型是地板,审美是天花板')⇄ 工具/模型/参数主导(堆模型能力、堆参数、堆 LoRA、以为换个大模型就行)**;**开源生态/本地可控(Stable Diffusion / ComfyUI / Flux / civitai / liblib 本地部署可定制可控可商用、显卡门槛)⇄ 闭源商业/易用黑盒(Midjourney / 可灵 / 即梦 / Runway 开箱即用但不可精控、按量付费、黑盒)**;**图像生成(T2I/I2I:Midjourney / SDXL / Flux)⇄ 视频生成(T2V/I2V:可灵 / Runway Gen-3 / Vidu / 即梦 / Sora,2024-2025 前沿从图迁移到视频)**;**生产力/商业量产(替代或增强传统设计/插画/电商/广告/影视分镜流程、降本提效、批量)⇄ 纯艺术创作/作者表达(个人风格、实验性、作品集)**;**效率/批量(一次出几十张筛选、商单走量、自动化 pipeline)⇄ 质量/精控(单张精修、商业可用级细节、修手修脸修穿帮)**。(b) 核心工作流 / pipeline(最标准、最易蒸高质量 + CLI 化)— 单图创作链:概念/参考收集(moodboard/风格定位/竞品)→ 模型工具选型(按可控性/风格/成本/可商用判断 MJ vs SD/Flux vs 国产)→ Prompt 与参数设计(主体/风格/光影/镜头/负向词/CFG/采样器/分辨率/种子)→ 首轮出图与方向筛选 → 可控迭代(ControlNet 控构图/姿态/线稿、LoRA 控风格/角色一致性、图生图重绘、inpainting 局部修)→ 放大超分与精修(高清放大/修手修脸/后期调色合成)→ 交付与参数留存(工作流文件/种子/参数复现)。视频创作链:分镜/脚本→首帧出图(图像链产出关键帧)→图生视频(运镜/时长/首尾帧/动态强度)→多镜头一致性(角色/场景/风格统一)→对口型/配音/配乐→剪辑合成→交付。ComfyUI 工程链:节点工作流搭建(加载器/采样/ControlNet/放大/面部修复节点)→ 参数化与复用→批量队列→工作流分享(civitai/openart workflow json)。(c) 工具栈 — 闭源图像(Midjourney v6/v7、DALL·E 3、Adobe Firefly、Ideogram、Recraft)、开源图像与底座(Stable Diffusion 1.5/SDXL/SD3、Flux.1 dev/schnell(Black Forest Labs)、ComfyUI(节点式)、Automatic1111/Forge WebUI、Fooocus)、可控生成插件(ControlNet、LoRA、IPAdapter、AnimateDiff、inpainting/outpainting、ReActor 换脸、面部修复 CodeFormer/GFPGAN、放大 ESRGAN/SUPIR/Topaz)、模型/资源社区(Hugging Face、Civitai、liblib 哩布、吐司 Tusi、openart)、视频生成(可灵 Kling、即梦 Dreamina/Jimeng、Runway Gen-3/Gen-4、Luma Dream Machine、Pika、Vidu、海螺 Hailuo、Sora、Wan 通义万相、MiniMax)、辅助(Magnific 放大、Krea、Photoshop/After Effects 后期、ChatGPT/Claude 写 prompt、reverse prompt 反推)。(d) 知识正典 — AIGC 创作 canon 横跨论文/工程/社区教程:奠基论文(DDPM、Latent Diffusion/Stable Diffusion(Rombach et al)、DiT、ControlNet(Zhang et al)、LoRA、DreamBooth、Textual Inversion、SDEdit、IP-Adapter、视频扩散 SVD/Sora 技术报告)、官方文档与模型卡(Stability AI、Black Forest Labs Flux、ComfyUI 文档、Midjourney docs、可灵/即梦官方教程、Hugging Face diffusers)、社区教程与工作流(ComfyUI 官方示例、civitai 文章、B站/YouTube 创作者长教程、openart workflow)、prompt 工程资源(Midjourney 风格库、提示词指南)。(e) figures/流派 — 模型/工具创造者(Midjourney David Holz、Stability AI Emad/Robin Rombach、Black Forest Labs(Flux,原 SD 团队)、ComfyUI comfyanonymous、ControlNet 张吕敏 Lvmin Zhang、AUTOMATIC1111、可灵/即梦/快手字节团队)、创作者 KOL 与教育者(Midjourney/SD 头部创作者、ComfyUI 工作流大神、AI 视频创作者、国内 B站/抖音 AIGC 教程作者、独立 AI 艺术家)、行业分析与评测(AI 工具评测、生成式 AI 创作生态观察者)。流派分歧:开源可控派(SD/ComfyUI/Flux 本地精控)vs 闭源易用派(MJ/可灵开箱即用)、工程化派(节点工作流/可复现/参数化)vs 玄学抽卡派(prompt 玄学/堆词/抽卡)、审美主导派('模型是地板审美是天花板')vs 工具主导派(堆模型堆参数)、图像派 vs 视频派、艺术创作派 vs 商业生产力派、国产工具派(可灵/即梦/liblib)vs 海外工具派(MJ/Flux/Runway)。(f) 行业话术/黑话 — 出图 / 抽卡 / 刷图 / 炼丹(训练 LoRA)/ 喂图 / 垫图(参考图/图生图)/ 控图 / 锁种子 seed / CFG / 采样器 sampler / 步数 steps / 重绘幅度 denoise / 提示词 prompt / 咒语 / 负向 negative / 权重 / tag / 大模型 checkpoint / 底模 / LoRA / ControlNet / 控线稿/openpose/depth / IPAdapter / inpainting 局部重绘 / outpainting 扩图 / 高清放大 / 超分 / 修手 / 崩手 / AI 味 / 风格 / 角色一致性 / 工作流 workflow / 节点 / 跑图 / 队列 / 文生图 T2I / 图生图 I2I / 文生视频 T2V / 图生视频 I2V / 首帧/尾帧 / 运镜 / 动态强度 / 时长 / 对口型 / 一致性 / 可商用 / 训练集 / 过拟合 / 翻车 / 穿帮。(g) 争议/批判 — 「版权与训练数据」(模型训练用未授权作品、生成图版权归属、可商用风险、洗图/伪原创)、「AI 替代创作者就业」(替代画师/插画师/设计师/摄影、行业冲击与转型)、「AI 味与审美趋同」(生成图同质化、套模板、缺乏原创审美)、「玄学 prompt 神话与割韭菜」('咒语'神秘化、'7天 AIGC 变现/月入过万'付费课割韭菜、抽卡当能力)、「工具快速迭代与淘汰焦虑」(模型月月换、工作流频繁失效、追新疲劳)、「开源 vs 闭源之争」(可控可商用 vs 易用黑盒)、「质量天花板」(修手修脸穿帮、长视频一致性、可控性仍有限)。(h) 大量隐性创作手艺 + 审美 + 工程 + 沟通软技能(prompt 的描述功底与审美词汇、参数与采样的手感、ControlNet/LoRA 的组合控制经验、节点工作流的搭建与调试、批量筛选的审美眼力、修图合成的后期功底、镜头语言与运镜设计、角色/风格一致性的控制、商业需求的翻译与交付、版权与可商用的判断)是高 tacit、靠大量实操跑图 + 审美积累 + 工程调试经验的核心。水分极高(大量'咒语速成/一键变现/AI 绘画割韭菜'营销
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。
Decide which model, effort level, and cascade shape each subagent gets, and how to keep improvement loops safe (evaluator-as-selector, stop on regression). Routes on measured cost-per-completed-task rather than per-token price, because a tier's token count varies more by task shape than price varies across tiers. Covers per-model effort semantics, the concision lever, cascade preconditions, context handoff, and watching a subagent fan-out live. Use when choosing a subagent's model or effort, when choosing how to escalate a failed attempt, or when asked which model or effort a task should get. Grounded in a 2026-07 calibration, a 2026-08 coding-cost study, a 2026-09 seeded-bug repair battery, a 2026-10 Haiku 5.5 ladder priced per spawn, and a 2026-10 retry-versus-escalation ladder on 295 SWE-bench Verified tasks; Managed Agents API specifics are operational, not calibrated.
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。
Judges whether a user's input suits the Vibe Creating style of video-prompt writing, and when it does, distills single-scene prompts, multi-shot descriptions, emotional imagery, or mixed input into prompts that are easier for a video model to generate from — while preserving any user-specified dialogue, voiceover, music, sound effects, and other hard constraints. Use when a user wants to turn an idea, story, feeling, or rough/over-specified prompt into a strong text-to-video prompt (Seedance, Sora, Kling, Veo, Runway, etc.), or asks to "rewrite", "improve", "clean up", or "vibe-ify" a video prompt. Do NOT use for long narrative films that need precise word-for-word dialogue sync, industrial shot lists meant to be executed verbatim, or functional/UI demos and step-by-step tutorials.
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。
Manage git worktrees across any repository with the `gwm` Rust binary (CLI + ratatui TUI). Use when the user asks to create / list / remove / bootstrap / switch / link worktrees, run a command across worktrees (`gwm exec`) or reclaim build artifacts (`gwm clean`), materialise a PR into a worktree (`gwm review`), drive a multi-repo workspace (`--workspace`), run the JSON daemon / statusline (`gwm daemon`, `gwm statusline`), list or pin AI-agent sessions per worktree (`gwm agents`, Claude Code / Codex / opencode / Mistral Vibe detection), seed config from a preset (`gwm init --preset`), diagnose with `gwm doctor`, drive tmux/zellij, or wire `gcd` via `gwm shell-init`. Also covers multi-forge (#419): GitHub via `gh` **or** GitLab via `glab`, the `forge` / `[forge_hosts]` keys, and `gwm trust add`. Triggers on `gwm`, `gwq`, `git worktree`, `.gwm.toml`, `forge`, `forge_hosts`, `glab`, `gwm trust add`, GitLab MR, `gwm create`, `gwm list`, `gwm exec`, `gwm clean`, `gwm review`, `gwm daemon`, `gwm statusline`, `gwm agents`, `gwm note`, `gwm bootstrap`, `gwm doctor`, `gwm switch`, `gwm tmux`, `gwm zellij`, `gwm link`, `gwm status`, `gwm shell-init`, `gcd`, `feat/#`, `fix/#`, GitHub issue/PR linking on a worktree.
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。
This skill channels the reasoning of Walter C. Willett, nutrition epidemiologist at Harvard University. Use this skill whenever you are asked to evaluate diets, give nutritional advice, critique food policy, or discuss the environmental impact of food systems. Trigger this skill for topics like macronutrient quality (fats vs. carbs), plant-based diets, the health impacts of red meat or dairy, seed oils, epidemiological methodology, and planetary health. Apply his frameworks to shift focus from macronutrient quantity to quality, evaluate foods using the 'Compared to what?' rule, and prioritize public health over personalized nutrition fads.
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。
Suede-owned community-growth discipline for member purpose, platform choice, seeding, rituals, moderation, health metrics, and earned advocacy. Use when starting, auditing, or growing a Discord, Slack, forum, subreddit, or comparable product community. NOT FOR: public social-channel content (use suede-social), referral-program mechanics (use suede-referrals), or customer-interview research (use suede-customer-research).
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。
Reverse-engineer a design system from a live website (public URL or localhost). Extracts colors, typography, spacing, shadows, radii, breakpoints, and component patterns using a headed Playwright browser. Captures screenshots of pages, components, and interactive states at real device resolutions. Produces structured design tokens and optionally seeds a Penpot project. **Triggers — use this skill when:** - User says "extract design system from [url]" - User asks to "reverse-engineer the styles from [site]" - User says "build a design system based on [website]" - User asks to "pull the design tokens from [url]" - User says "analyze the design of [site]" - User asks to "import styles from [website] into Penpot" - User points at a URL and asks about its colors, fonts, spacing, or components
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。
Use when the user wants to know if something works — the answer requires running code, not analyzing it. Output is a verdict backed by evidence: passed, failed, or broken. Primary triggers: 'run the tests', 'does X still work after my change?', 'did the merge break anything?', 'verify the fix worked', 'check if the endpoint returns X', 'confirm nothing regressed', 'run tests/unit/test_foo.py', 'let me know the results', 'make sure my changes didn't break anything'. Hard stops — do NOT use for: reviewing test code for quality/coverage gaps, debugging why test infrastructure/databases/seed scripts are misbehaving, writing or fixing tests, diagnosing root causes of unexpected behavior. The deciding question: is the user asking for the result of executing something, or asking for help understanding/analyzing/improving something? If it's the latter, use diagnose or review-code instead.
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。
Run 150+ AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating Twitter. Triggers: inference.sh, infsh, ai model, run ai, serverless ai, ai api, flux, veo, claude api, image generation, video generation, openrouter, tavily, exa search, twitter api, grok
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。
Use when starting any game task, before writing tests - find out which editors and runners exist on this machine, keep gameplay rules in engine-independent classes with an injected clock and seeded RNG, and report exactly what could not run.
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。
Use when you are about to hand off a change a player can see - the exact steps to look at it running (web game in the browser at two viewports plus a seeded Playwright smoke run for input and console errors; engine games through a headless frame capture), the checklist, and how to report what could not be observed.
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。
Use when a case needs data, a user/role, or a third-party dependency - seeding through the product first, test credentials, namespacing on shared environments, and stubbing an external HTTP service by hand
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。
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.
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。
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.
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。