923 个 · 按相关度排序
当使用者说"我想写一首关于X的歌"、"这首歌想表达Y"、"帮我想想这首歌写什么"、"疗愈主题的歌该怎么切入"时使用，适用于只有主题词或一句念头、还没定具体处境的时候；处境和字数骨架都已齐、只差句子时改用 adversarial-lyric-writer。动笔写句子之前先定四样东西：这首歌的具体处境（谁、在什么状况、发生了什么变化）、一套只属于同一个世界的意象系统、情绪弧线的起点转折点终点、五条 hook 候选。派 sonnet 子代理并行提三个不同切入角，主 Agent 收敛。只问两个问题：唱给谁、有没有真实的画面可用。不替使用者编经历，不把"疗愈""成长"这类效果词当成主题。
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当问「这条公式怎么来的」「为什么长这样」，或说「帮我推导／推出 X 公式」时使用。从定义或守恒律出发重建标准公式，每一步标出用的是哪条原理、这一步在物理上做了什么；假设写在它真正被用到的那一步，不堆在开头。终式可用 scripts/compare_formula.py 与标准式做符号比对。会被评分的推导：结构与理由可以给，代数由本人做。要逐步核验一份已写好的推导，用 derivation-step-checker。
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当使用者说"帮我填词"、"按这个字数模板写歌词"、"用多Agent对抗式写词"、"这首副歌帮我想几句"时使用，前提是字数骨架和这首歌写什么都已经有了；只有主题、还没定写什么时先用 lyric-concept-builder。拿一份字数骨架和意象系统，派三个 sonnet 子代理按不同路子并行独立起草（场景派 / 口语派 / 意象派），再派一个红队子代理逐句挑毛病，主 Agent 按句裁决拼稿，最后统一辙口与意象。收敛判据卡死：字数用 lyric-doctor 的脚本对模板数、每段同辙、hook 不含陈词、主歌二对主歌一有推进。不抄现有歌词，不替使用者决定这首歌要说什么。
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当需求还只是"帮我写个东西""让 AI 做这个任务"这种一句话时使用。用至多 3–5 个高杠杆追问把它补成一份可交付的任务简报——目标、产物、受众、已有素材、约束、验收标准、不做什么、待确认假设，外加一段可直接粘贴的执行 prompt。简报的九个标题保持英文（内容用什么语言都行），字段完整性由 scripts/check_brief.py 校验。产出不绑定任何一家模型，人或 Agent 都能照着执行。不适用于：写歌交给 lyric-concept-builder，复习计划交给 deadline-to-study-plan，建模题交给 modeling-problem-reading-coach，物理题交给 physics-problem-router；使用者坚持直接要成品、一个问题都不肯答时也不用本 skill。
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Teach the user a new skill or concept, within this workspace.
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Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack."
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Consolidate PostHog error tracking issues that are the same actual error reported under different fingerprints. Use when the user asks "why do I have so many TypeError issues that look the same?", "merge these duplicates", "stop splitting this error into new issues", or wants to clean up fingerprint sprawl. Decides between a one-shot merge of existing issues and a durable grouping rule that keeps future events from creating new fingerprints. Does NOT group conceptually similar bugs across different runtimes, SDKs, or call sites.
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Designs genomics experiments so technical nuisance variation (batch, lane, plate, flow cell, operator, reagent lot, processing day) is balanced against the biological variable of interest and therefore estimable rather than confounded, using constrained sample-to-batch assignment (designit, OSAT), the confounder/mediator/collider distinction, and the principle that no post-hoc correction recovers a fully confounded design. Covers detecting hidden batches with surrogate variable analysis, a decision table for downstream correction (ComBat-seq, RUVSeq, SVA) whose execution is deferred to differential-expression/batch-correction, and reproducibility metadata. Use when assigning samples to sequencing batches/lanes/plates, avoiding batch-condition confounding, deciding whether a design is salvageable by correction, choosing a correction method, or estimating the number of hidden batches. For the experimental unit, randomization, and blocking concepts see experimental-design/randomization-blocking.
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TOP PRIORITY skill — find and immediately fix or remove every piece of wrong, outdated, or redundant information in ToolUniverse docs. Wrong code, broken links, incorrect counts, and overlapping instructions must be fixed or removed — never left in place. Runs five phases: (D) static method scan, (C) live code execution, (A) automated validation, (B) ToolUniverse audit, (E) less-is-more simplification. Core philosophy: each concept appears exactly once; remove don't add; no emojis; single setup entry point. Use when reviewing docs, before releases, after API changes, or when asked to audit, fix, or simplify documentation.
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Maps metabolomics results to biological pathways via over-representation (ORA), metabolite-set enrichment (MSEA/QEA), mummichog/PSEA on raw m/z peaks, and network-diffusion enrichment (FELLA), with correct background-set construction and honest interpretive ceilings. Use when interpreting differential metabolites or an untargeted LC-MS feature table in pathway context, choosing ORA vs MSEA vs mummichog vs topology, or setting the reference/background set. For annotation confidence levels feeding ORA see metabolomics/metabolite-annotation; for gene-set concepts see pathway-analysis/go-enrichment and pathway-analysis/gsea; for joint gene+metabolite pathways see multi-omics-integration/mofa-integration.
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Working Backwards PRFAQ challenge to forge product concepts. Use when the user requests to 'create a PRFAQ', 'work backwards', or 'run the PRFAQ challenge'.
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Design proof-of-concept frameworks for AI projects. TRIGGERS - Use when user needs help with ai-poc-framework related tasks.
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Designs genomics experiments so technical nuisance variation (batch, lane, plate, flow cell, operator, reagent lot, processing day) is balanced against the biological variable of interest and therefore estimable rather than confounded, using constrained sample-to-batch assignment (designit, OSAT), the confounder/mediator/collider distinction, and the principle that no post-hoc correction recovers a fully confounded design. Covers detecting hidden batches with surrogate variable analysis, a decision table for downstream correction (ComBat-seq, RUVSeq, SVA) whose execution is deferred to differential-expression/batch-correction, and reproducibility metadata. Use when assigning samples to sequencing batches/lanes/plates, avoiding batch-condition confounding, deciding whether a design is salvageable by correction, choosing a correction method, or estimating the number of hidden batches. For the experimental unit, randomization, and blocking concepts see experimental-design/randomization-blocking.
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Create hand-drawn style diagrams using Excalidraw JSON format. Generate .excalidraw files for architecture diagrams, flowcharts, sequence diagrams, concept maps, and more. Files can be opened at excalidraw.com or uploaded for shareable links.
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Gera imagem por IA via Ideogram, Leonardo ou Flux usando os scripts do plugin, ou entrega o prompt otimizado quando não há chave. Use quando o usuário disser "gerar imagem", "criar ilustração", "imagem por IA", "Ideogram", "Leonardo", "Flux", "preciso de uma foto que não temos", ou quando creative-concept marcar um ativo como "gerar". Skill central deste plugin. Toda chamada gasta crédito e exige confirmação prévia.
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Traduz copy aprovada em conceito visual — ideia central, hierarquia, sistema de peças e especificação de ativos. Use quando o usuário disser "como fica visualmente", "conceito da campanha", "direção de arte", "qual a ideia da peça", "transformar a copy em criativo", ou antes de montar qualquer coisa no Figma. É a ponte entre pwdev-copy e a produção.
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YC Office Hours — two modes. Startup mode: six forcing questions that expose demand reality, status quo, desperate specificity, narrowest wedge, observation, and future-fit. Builder mode: design thinking brainstorming for side projects, hackathons, learning, and open source. Saves a design doc. Use when asked to "brainstorm this", "I have an idea", "help me think through this", "office hours", or "is this worth building". Proactively invoke this skill (do NOT answer directly) when the user describes a new product idea, asks whether something is worth building, wants to think through design decisions for something that doesn't exist yet, or is exploring a concept before any code is written. Use before /plan-ceo-review or /plan-eng-review. (gstack)
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Provide advisory guidance for the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration in AEMaaCS cloud workflows only, with public-doc citations and cloud-specific MCP verification plans. Use for conceptual questions such as `statfileslevel`, filter rules, URL decomposition, cache invalidation behavior, rewrite behavior, and security headers.
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[BETA] Expert assistance for the Adobe I/O CLI plugin `@adobe/aio-cli-plugin-aem-rde` — the `aio aem rde` / `aio aem:rde` command tree used to deploy, inspect, log-tail, snapshot, and troubleshoot AEM Rapid Development Environments (RDEs). Activate ONLY when the user explicitly references RDE concepts: 'AEM RDE', 'Rapid Development Environment', `aio aem rde`, `aio aem:rde`, `aem-rde`, RDE snapshots, RDE deploy/install, `rde install`, `rde inspect`, `rde status`, `rde history`, `rde reset`, the `@adobe/aio-cli-plugin-aem-rde` package, or Cloud Manager program/environment configuration that is specifically for an RDE environment. Do NOT activate on generic AEMaaCS phrases like 'deploy to AEM Cloud', 'push my bundle', 'tail the publish log', 'cloud sandbox', or unqualified 'dispatcher-config / frontend / env-config deployments' — those belong to Cloud Manager pipelines, not RDE. This skill is in beta. Verify all outputs before applying them to production projects.
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Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.
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Elite mobile app image-generation skill for creating premium, app-native screen concepts and flows. Designed for iOS, Android, and cross-platform mobile products. Prioritizes clean hierarchy, comfortably readable text, strong multi-screen consistency, controlled color palettes, non-generic creative direction, textured surfaces, image-led composition, tasteful custom iconography, and clean phone mockup framing. By default, screens should be shown inside a subtle premium iPhone or similar phone mockup with a visible frame, while the main focus stays on the app content itself. This skill generates images only. It does not write code.
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Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.
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DALL-E 3 image generation workflow for this repo MCP server. Use for dalle3, DALL-E 3, OpenAI image generation, concept art, UCUF reference exploration, UI icon, badge, card art, prompt drafting, and saving generated images to local files under artifacts/ui-source or other workspace paths.
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GPT Image 2 image generation workflow for this repo MCP server. Use for gpt-image-2, OpenAI image generation, concept art, UCUF reference exploration, UI icon, badge, card art, prompt drafting, transparent-background asset drafts, and saving generated images to local files under artifacts/ui-source or other workspace paths.
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