The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.
Every Agent Skill we could find on GitHub, deduplicated by content. 79 600 files from 1 763 authors, of which 61 947 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.
Add or modify FlashDreams video post-processing processors, sessions, presets, and runner stream wiring. Use when implementing a new VideoPostProcessorConfig / VideoPostProcessor / VideoPostProcessorSession, registering a --postprocess.preset entry point, changing VideoPostprocessStream behavior, or reasoning about streaming buffering, layouts, per-view processing, distributed execution, or postprocess tests.
Maintain FlashDreams's OSS-release state — the LICENSE / NOTICE / THIRD-PARTY-NOTICES / REUSE.toml / LICENSES/ / CONTRIBUTING.md collateral that satisfies OSRB Bug 6107043, the per-file SPDX headers, the third-party dependency manifest in THIRD-PARTY-NOTICES, and the pyproject.toml + uv.lock dependency pins. Use when adding or upgrading a runtime dependency, vendoring third-party source into the repo, adding a new first-party source file (any .py / .pyx / .pyi / .c / .cc / .cpp / .h / .hpp / .cu / .cuh / .sh / .proto / Dockerfile), reviewing whether a change requires reopening an OSRB bug or filing a self-cert, or triaging a reuse-lint CI failure.
Write Python docstrings and inline comments matching the flashdreams house style — SPDX header, one-line module docstring, Google-style function docstrings (Args/Returns/Raises), PEP 257 attribute docstrings on dataclass/class fields *and on module-level constants*, double-backticks for code references, imperative first sentences, and signpost-style inline block comments (kept, not stripped, on a tightening pass). Use when authoring or editing any .py file under flashdreams/, when adding a new module/class/function/field/constant, when polishing comments, or when the user asks about docstring or comment style.
Build and maintain a Markdown guide that helps humans understand a repository through real behavior, concepts, and evidence. Use when a user asks to understand a repo, generate or update repo-docs, answer repo-architecture/onboarding questions, seed docs for a new project, sync docs after code changes, or delete generated repo docs.
Generate and maintain repo-docs with Chinese as the primary reader language while preserving source identifiers for lookup. Use when the user asks for Chinese repo docs, mentions repo-docs-zh, wants repo documentation in Chinese, or wants an existing repo-docs package localized for Chinese readers.
Your team's shared, AI-ready knowledge base — people, companies, meetings, SOPs, and decisions structured so Claude can answer questions on your team's behalf. Team-scope sibling to second-brain (which is personal-scope). Seven modes — capture (drop something into the right structured dir), compile (process into wiki pages, update INDEX.md), query (answer from the corpus with trust weighting, save to outputs/), review (triage queue — verify / deprecate / supersede unreviewed and stale captures so wrong info never becomes context), lint (orphans / stale / contradictions / gaps), connect (suggest new wikilinks), search (quick lookup). Structured raw dirs (people/, companies/, meetings/, sops/, decisions/, customer-language/, recurring-questions/, sales-objections/) instead of second-brain's flat type-prefixed raw/. Multi-author aware — every capture stamps author + timestamp + trust status. Optional auto-sync from Fathom/Gong/Granola call transcripts, Slack/email exports, CRM. Defaults to a vault at ${COMPANY_BRAIN_VAULT:-$HOME/Documents/CompanyBrain}/. Triggers on "/company-brain," "/cb," "capture this into the team brain," "log this meeting," "add this person to the team brain," "save this SOP," "compile the company wiki," "query the team brain," "what does the team know about X," "review the company brain," "cull the team brain," "lint the company brain," "who's the internal expert on X.
When you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any \"I need to actually understand X.\" Combines WebSearch, WebFetch, agent-browser, /last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on \"/deep-research,\" \"research X,\" \"investigate X,\" \"do a deep dive on X,\" \"look into X,\" \"what's actually happening with X,\" \"due diligence on X,\" \"validate this market.\" Differs from a one-shot WebSearch: this is multi-pass with verification.
Monthly CFO workflow for a company or agency — pull raw data from bank + payment processor + payroll + expense management, categorize and reconcile, compute end-of-month cash via transaction-sum method, update a scenario projector for forward forecasting, write the monthly snapshot report, surface decisions to leadership. Modes — monthly (default; the standing report), weekly (thin cash pulse), scenario (ad-hoc modeling in the projector), pickup (resume where the prior run left off). Anonymized team-scope sibling to personal-cfo (which handles personal household finances). Composes with company-brain (report gets stored + wiki-indexed there), toolify (wire company-specific data sources), loopify (schedule the monthly + weekly runs). Triggers on "/company-cfo," "/cfo," "monthly cash report," "do the CFO snapshot," "CFO monthly," "let's run CFO," "cash projection," "runway forecast," "monthly financials," "cash pulse.
When you have a decision to make and want a structured workflow that picks the load-bearing questions, walks through them, reaches a call (or "wait"), and archives the rationale for future reference. Based on the 37signals Guide to Making Decisions (38 questions) plus house additions like Q39 opportunity cost ("what does saying yes displace?"). Triages to 6–8 relevant questions per decision instead of forcing the full set. Archives every decision to ~/.config/makerskills/decide/archive/ with a revisit date so you can check later whether the call was right. Triggers on "/decide," "help me decide," "should I [X]," "I need to make a decision about," "stuck on a decision," "deciding between," "go/no-go on," "what should I do about." This is both the decision-making workflow AND the decision log — making the decision is the act of logging it.
When you want to brainstorm and check available .com domains for a new project — brand naming, aftermarket pricing (HugeDomains / Afternic / Sedo / Dan), USPTO trademark screening, and social handle availability. Built on Laura Roeder's \"work backwards from availability, not from a name you fell in love with\" methodology. Uses Vercel CLI + whois + Domainr API + Namecheap API + agent-browser for the pieces each tool actually reliably supports (multi-tool ensemble because no single tool covers everything cleanly). 11-step workflow: budget → brainstorm → primary availability check → whois cross-check → Domainr aggregation → Namecheap price → aftermarket sweep → bucket → negotiate → NAME research (trademark + socials) → buy. Triggers on \"/domain,\" \"find a domain,\" \"check domain availability,\" \"brainstorm a domain,\" \"what .com is available for X,\" \"domain hunt,\" \"name my project,\" \"is X.com available,\" \"aftermarket price on X.com,\" \"trademark check for X.\
Gary Vaynerchuk's jab-jab-jab-right-hook framework applied to a personal portfolio rotation on X and LinkedIn. Jabs = build-in-public + educational (value). Hooks = promo (the ask). Each property in the user's configured portfolio (see `~/.config/makerskills/jab-hook/properties.yaml`) gets a hook at least once every ~3 weeks; jabs fill the rest. Drafts go into the user's Typefully workspace via MCP. Modes — plan (7-day plan), pick-next (single post), audit (coverage report), draft (specific post). Triggers on "/jab-hook," "what should I post," "plan my socials," "next promo," "next jab," "next hook," "social rotation," "promote [property]," "BIP post," "audit my socials," "what haven't I posted about.
When you want to pressure-test a potential new business, product, or side project against the serial-founder filter. Not \"marketing ideas for a product\" (that's marketing-skills:marketing-ideas) — this is \"should this business exist + can you win it.\" Runs the idea through a structured framework (problem, audience, wedge, monetization, moat, portfolio fit, distribution, energy fit, opportunity cost), checks domain availability via /domain, optionally triggers /deep-research for market validation, and outputs a viability brief: build / sleep on it / pass. Archives every idea to ~/.config/makerskills/business-brainstorm/archive/ so past work is searchable. Triggers on \"/business-brainstorm,\" \"/brainstorm,\" \"new business idea,\" \"should I build X,\" \"pressure test this idea,\" \"validate this idea,\" \"is X a good business,\" \"what about a [type] for [audience].\
When you want to set up an agent loop, cron-scheduled task, or recurring workflow that runs autonomously in Claude Code. Judgment layer on top of ScheduleWakeup, CronCreate, and the /loop skill — decides whether to use dynamic pacing (self-scheduling wake-ups), cron scheduling (fixed intervals), or a one-shot loop; tunes delay to avoid the 5-minute cache-miss cliff; designs idempotent loop bodies; sets bail-out conditions so loops don't run forever. Examples of loops to loopify — weekly review pulse, daily brief generation, hourly monitoring of a metric, periodic vault compilation, upstream-check for an adapted skill, sponsorship-pipeline refresh, YouTube-transcript-batch-download, morning startup routine. Triggers on "/loopify," "set up a loop," "schedule this task," "run this daily," "run this weekly," "cron this," "make this recurring," "automate this on a schedule," "keep this running until X." Part of the -ify trifecta (skillify / toolify / loopify) for extending Claude Code. NOT for authoring a new skill — that's skillify. NOT for adding a tool/integration — that's toolify.
When you want to model personal financial scenarios — house purchase + rental income (ADU, bedroom rentals, house-hacking), renovation budgets, monthly cash flow forecasts, big-purchase decisions, savings/investment what-ifs. For personal life: a household (you + partner), household budgets, real-estate decisions. v0.1 ships with the house scenario template (purchase + rental scenarios) as the first use case. Architected so other personal-finance scenarios (refi, car, education, retirement, side income) slot in as additional templates. Outputs scenario comparison tables in markdown. Saves every scenario to ~/Documents/personal-cfo/ with an index at ~/.config/makerskills/personal-cfo/archive/ for revisit + comparison. Composes with decide (formalize the call after modeling), deep-research (rental comps, mortgage rates, market data), business-brainstorm (when the scenario is a small business / side hustle), second-brain (capture the analysis to outputs/). Triggers on \"/personal-cfo,\" \"model this scenario,\" \"house math,\" \"rental forecast,\" \"monthly cash flow,\" \"what if I rent out the ADU,\" \"compare these housing scenarios,\" \"should we buy this house,\" \"house-hack math,\" \"renovation budget.\
When you want to clean and reformat content (usually from your terminal) for pasting into Slack, Notion, Twitter/X, LinkedIn, email, GitHub, or plain text. Strips ANSI codes, box-drawing chars, terminal prompt artifacts, and applies destination-specific formatting. Default input is the clipboard (read via `pbpaste`); default output is both the clipboard (`pbcopy`) and a chat preview. Triggers on "/paste", "/paste [destination]", "clean this for X," "format for slack/notion/twitter/linkedin/email/github," "render as markdown," "paste-ready," "strip formatting," "make this copy-pastable." Default destination is plain. Also scans for secrets (API keys, tokens, .env values) and warns before copying anything sensitive.
When you want to read and extract structured notes from a book — PDF, EPUB, MOBI, markdown, .txt, pasted text, or URL to a public-domain work. Reads in chunks (by chapter when a TOC exists, by 50-page blocks otherwise), extracts per-chapter TL;DR + key concepts + quotes + action items + frameworks, and offers to capture to second-brain raw/ as a highlights- file. Four modes — notes (default, chapter-by-chapter), summary (whole-book TL;DR + 3–5 takeaways), quotes (pull-quote highlights only), study (notes + Q&A spaced-rep prep). Triggers on "/read-book," "read this book," "extract notes from this PDF," "what's in this book," "summarize this ebook," "pull quotes from this." Sibling to watch-video (same content-consumption pattern, different medium).
When you want to capture into, compile, query, lint, or connect your personal Second Brain. Wraps the Karpathy LLM Wiki schema (Obsidian or any markdown vault) — raw/ (unprocessed sources), wiki/ (AI-compiled interlinked topic pages), outputs/ (generated artifacts). Tool-agnostic in design but defaults to a vault at ${SECOND_BRAIN_VAULT:-$HOME/Documents/SecondBrain}/. Six modes — capture (drop something into raw/), compile (process unprocessed raw files into wiki pages, update INDEX.md), query (answer a question from the wiki, save to outputs/), lint (orphans / contradictions / stale / unprocessed raw / topic gaps), connect (suggest new wikilinks between pages), search (quick lookup). Triggers on "/second-brain," "/sb," "capture this," "save this to my brain," "compile the wiki," "process raw notes," "query my wiki," "ask my brain," "lint the wiki," "find connections," "search my notes." Complements deep-research (external corpus) — this is the internal corpus.
When you want to create, adapt, or update a Claude Code skill in one of your sibling repos (list your own repos in ~/.config/makerskills/skillify/repos.yaml; defaults to makerskills). Routes to the right mode automatically. Modes — CREATE (from-chat / from-video / from-dump / from-scratch) turns a workflow, brief, recording, or fresh idea into a new skill. ADAPT ports an external skill (GitHub URL, agentskills.io, local disk) into your namespace with three-bucket classification (keep/adapt/add) + license check + attribution. UPDATE improves existing skills from learnings with cross-skill propagation, memory-vs-skill triage, and semver discipline. Defers to Anthropic's guidance (compound-engineering:create-agent-skill, compound-engineering:skill-creator, compound-engineering:heal-skill) for schema and best-practice depth. Triggers on "/skillify," "create a skill," "make this a skill," "skill from this chat," "extract a skill from what we've been doing," "adapt this skill," "port this skill," "fork this skill," "borrow this skill," "update X skill," "apply this to the relevant skills," "propagate this learning," "improve [skill]," "fix [skill]," "iterate on [skill]." Part of the -ify trifecta (skillify / toolify / loopify) for extending Claude Code.
When you want to manage projects across your businesses using a kanban + Eisenhower methodology. One kanban per business (whatever portfolio of businesses, projects, or initiatives you run). Tool-agnostic — connects via API/MCP to whatever PM tool each business uses (Notion, GitHub Projects, Plane, Linear, Obsidian file-based, or manual mode). Async-first output. Six modes — setup (scaffold a new board for a business), triage (Eisenhower-sort the backlog), next (pick the next thing to work on, single board or across all), status (paste-ready async snapshot), unblock (diagnose Review/Blocked column), weekly (Friday pulse + week planning). Triggers on "/pm," "/pm setup," "/pm triage," "/pm next," "/pm status," "/pm unblock," "/pm weekly," "what should I work on next," "kanban status," "Eisenhower this," "triage my backlog," "what's blocked.
When you or another skill needs to fetch the content of a social media post by URL — tweet, X thread, LinkedIn post, Instagram post, TikTok video, Bluesky post, Reddit thread, Mastodon status, Threads post, Hacker News thread. Returns normalized structured data (author, posted_at, text, engagement counts, media URLs, replies if requested) regardless of platform. Tries strategies in order: direct API (Bluesky, Mastodon, HN, Reddit), agent-browser with modal dismissal (LinkedIn, X preview), Wayback Machine (older posts), paid APIs (ScrapeCreators / Apify — only if env keys present). Triggers on \"/social-fetch <url>,\" \"fetch this tweet,\" \"fetch this post,\" \"what does this LinkedIn say,\" \"read this thread,\" \"pull this post.\" Used by deep-research (citing specific posts), jab-hook (inspiration account analysis), business-brainstorm (competitor / operator commentary).
When you want to draft, update, convert, or export a slide deck for a React/Next.js slide system (${SLIDE_DECK_REPO:-$HOME/code/your-slide-deck-site}/src/app/slides/). Writes TypeScript Slide[] arrays using your primitives (Eyebrow, Heading, Accent, Body, BulletList, Divider, TwoCol, GradientText), 12 cycling brand gradients, optional sections for "where am I" context, and speaker notes. Inspired by zarazhangrui/frontend-slides — "show, don't tell" applied to narrative (presents 3 angles, you pick) plus density modes (speaker-led vs reading-first). Four modes — new (draft from brief), update (modify existing, with overflow guards), ppt (convert legacy PPTX → React deck), export (Playwright snapshot existing React deck to standalone HTML, PDF, or Vercel URL — keeps brand). Triggers on "/slide-deck," "/slides new," "/slides export," "/slides update," "/slides ppt," "draft a deck," "deck for [topic]," "talk on [topic]," "keynote on [topic]," "internal deck for [audience]," "convert this pptx," "export this deck.
When a solution seems impossible and the path forward is blocked — the antidote to any roadblock or wall. Refuses to take no for an answer: classifies what kind of \"no\" you actually hit, then runs targeted lateral-thinking techniques (assumption autopsy, inversion, first principles, constraint toggling, analogical transfer, and more from a 10-technique inventory) until the wall cracks or is proven load-bearing. Generates a minimum of 10 angles before evaluating any. AGENTS: use this on yourself mid-task — when an API doesn't support what you need, an approach has failed twice, or a \"that's not possible\" / \"the only option is\" sentence is forming in your response, run the fast path BEFORE reporting a dead end; every dead-end report should arrive with tried-angles receipts. Archives every wall to ~/.config/makerskills/unstuck/archive/ so you learn which techniques crack YOUR walls. Sits upstream of decide: turns \"impossible\" into 2–3 viable angles, then decide picks one. Triggers on \"/unstuck,\" \"I'm stuck,\" \"this seems impossible,\" \"we hit a wall,\" \"there's no way to,\" \"they said no,\" \"dead end,\" \"out of options,\" \"I've tried everything,\" \"work around this,\" \"think outside the box.\
When you want to extract content from a video — YouTube, Loom, Vimeo, Riverside, Zoom recording, local MP4, X/IG video, anything yt-dlp supports. Three depth modes user picks per invocation — transcript (just words, fast/free), visual (transcript + ffmpeg frame extraction + Claude vision pass on key moments), multimodal (Gemini native video ingestion if $GEMINI_API_KEY set, else dense Claude vision). Uses MLX-Whisper local on Mac for transcription, falls back to platform-provided transcripts when available (Loom, Riverside, YouTube auto-subs). Saves to ~/Documents/videos/<source>-<slug>-<date>/ and optionally captures summary to second-brain raw/ as call-/meeting-/note-. Triggers on "/watch-video <url>," "watch this video," "transcribe this loom," "analyze this video," "summarize this recording," "key moments from this," "what happened in this video." This skill replaces and broadens the prior youtube-transcript skill.
When you want to integrate an external tool, API, MCP server, or service into a project — the wizard walks you through auth, config, env vars, client wrapper code, example usage, and (optionally) a smoke-test. Scoped to Next.js and Rails projects (the two primary stacks). Interactive Q&A pattern — starts with the tool name, asks structured questions until the integration is fully specified, then scaffolds files. Examples of tools to toolify — Stripe, Kit, Sanity, Notion, Neon, Supabase, Fathom, Rewardful, SavvyCal, Riverside, ScrapeCreators, Anthropic, OpenAI, Gemini, Twilio, Resend, Postmark, Vercel Blob, custom internal APIs. For MCP servers specifically, also handles the .mcp.json wiring. Triggers on "/toolify," "integrate X," "add X to this project," "wire up X," "set up the X integration," "hook up X," "connect X," "add MCP for X." Part of the -ify trifecta (skillify / toolify / loopify) for extending Claude Code. NOT for adding new SKILL.md files — that's skillify. NOT for cron/agent loops — that's loopify.
> Diagnose and fix Cosmos3 environment, installation, and runtime errors. Use when the user encounters an ImportError, ModuleNotFoundError, CUDA error, Docker error, checkpoint download failure, or any traceback during setup or inference.
> Guide users through Cosmos3 installation, environment setup, checkpoint downloading, and verification. Use when the user asks "how do I install cosmos3", "how do I set up the environment", "how do I download checkpoints", "how do I use Docker", or any question about getting the package running for the first time.
> Diagnose and fix Cosmos3 environment, installation, and runtime errors. Use when the user encounters an ImportError, ModuleNotFoundError, CUDA error, Docker error, checkpoint download failure, or any traceback during setup or inference.
> Navigate the Cosmos3 package codebase to find where parameters, configs, defaults, scripts, and documentation live. Use when the user asks "where is X in cosmos3", "how do I find the config for Y", "where are the defaults", "where do I change a parameter", or any question about locating files, modules, or settings. Also use when the user opens or edits files and needs orientation.
> Guide users through running Cosmos3 inference — offline batch generation, online serving with Ray and Gradio, parallelism options, input formats, sampling parameters, and prompt upsampling. Use when the user asks "how do I run inference", "how do I generate a video", "how do I serve the model", "what parameters should I use", or any question about running the model to produce outputs.
> preparing the example dataset and Wan2.2 VAE, converting the base checkpoint to DCP, launching distributed training (paired launch shell recommended, raw `torchrun` as an alternative), running T2V/I2V/V2V inference with the trained DCP checkpoint, and optionally exporting it to Hugging Face safetensors. Use when the user asks how to post-train Cosmos3, fine-tune on a custom video dataset, export a trained checkpoint, or invoke one of the recipe launch shells (`launch_sft_vision_nano.sh`, `launch_sft_llava_ov.sh`, `launch_sft_videophy2_nano.sh`, plus the `_super` LoRA variant) — or any question about `cu130-train` / `cu128-train`, `convert_model_to_dcp` / `export_model` / `train`, or SFT output paths. For dataset captioning / JSONL assembly, see `docs/dataset_jsonl.md`.
> Navigate the Cosmos3 package codebase to find where parameters, configs, defaults, scripts, and documentation live. Use when the user asks "where is X in cosmos3", "how do I find the config for Y", "where are the defaults", "where do I change a parameter", or any question about locating files, modules, or settings. Also use when the user opens or edits files and needs orientation.
> preparing the example dataset and Wan2.2 VAE, converting the base checkpoint to DCP, launching distributed training (paired launch shell recommended, raw `torchrun` as an alternative), running T2V/I2V/V2V inference with the trained DCP checkpoint, and optionally exporting it to Hugging Face safetensors. Use when the user asks how to post-train Cosmos3, fine-tune on a custom video dataset, export a trained checkpoint, or invoke one of the recipe launch shells (`launch_sft_vision_nano.sh`, `launch_sft_llava_ov.sh`, `launch_sft_videophy2_nano.sh`, plus the `_super` LoRA variant) — or any question about `cu130-train` / `cu128-train`, `convert_model_to_dcp` / `export_model` / `train`, or SFT output paths. For dataset captioning / JSONL assembly, see `docs/dataset_jsonl.md`.
> 把长视频按 Agent 选择的原片区间剪成短片。作为两阶段创作流程中的剪辑环节,读取 clip_plan.json 与源视频, 输出 edited_source.mp4;随后 Agent 按输出时间线写 narration.json。单独调用且未传 --no-narration-map 时, 仍支持旧版单阶段路径,把原片时间的 narration.json 映射为 narration_mapped.json。 触发词:视频剪辑、剪辑式解说、video cut、clip plan、拼剪。
> 把带时间戳的 narration.json 合成为中文解说音频。使用 MiMo TTS(mimo-v2.5-tts)逐段生成语音, 按时间窗动态适配语速并处理响度;输入输出时间线上的旁白,产出 tts_segments 与 tts_meta.json。 旧版直接剪辑路径也可显式传入 narration_mapped.json。触发词:配音、语音合成、TTS、解说配音、 voiceover、text to speech、旁白配音。
> 对已完成分析的视频进行导演与剪辑策划,再写带时间戳的中文解说并校验。work_dir 已包含 agent_narration_brief.md 与 vlm_analysis.json 时使用。适用于故事方向、片段选择、画面/原声/旁白分工、 解说写作与复核。输入 work_dir 中的理解索引;输出 recap_story_plan.json、visual_audio_board.json、 cut 模式需要的 clip_plan.json,以及通过校验的 narration.json。触发词:解说词、写解说、视频旁白、 narration script、写稿、解说文案、剪辑思路、导演思路。
> 合成视频解说最终成片:把旁白音频铺到源视频上,按旁白窗口压低原声,生成 SRT / ASS 字幕并可烧录, 最后做响度标准化。作为最终合成阶段使用。输入源视频、tts_meta.json 与旁白位置; 输出 recap 成片和字幕。触发词:视频合成、混音、字幕、压字幕、assemble video、mux、ducking、subtitles、成片。
> 从输入视频端到端生成中文解说成片。用户提供 .mp4 / .mov / .mkv / .webm,并要求添加旁白、 配音、总结、短剧/电视剧/电影/纪录片/科普解说时使用。负责编排 video-* 技能链:视频理解 → Agent 制定故事与视听方案 → 剪辑 → 配音 → 合成。触发词:视频解说、视频旁白、生成解说、 视频 recap、video recap、voiceover、narration、auto-dub、recap。
国内自媒体发布前风险自审与保意修复:审口播稿、文章、图文笔记、字幕、封面文字能不能发抖音/小红书/微信视频号,给出具体位置、依据和可直接替换的改稿;被限流/删除/处罚后帮你复盘归因;你的行业敏感词、误报白名单和踩坑案例会沉淀成个人规则库,越用越准。Use when 用户说"能不能发""审一下稿子""查违禁词/敏感词""会不会限流/被限流了""帮我改成能发的版本""发布前检查""被平台处罚/删除了""帮我盯着这个词""导入违禁词表"。Not for 海外平台(X/YouTube)内容审核、起号涨粉策略、写稿创作本身。
Create, edit, caption, voice, assemble, validate, and export editable video timelines with Timeline Studio. Use for automatic video editing, AI voiceover videos, subtitle generation, image-to-video assembly, short-form video production, deterministic local video rendering, .timeline project automation, or end-to-end editor evaluation in Codex, Claude Code, Copilot, and Gemini CLI.
A comprehensive guide and reference for building agents using LangGraph 1.0, including ReAct agents, state graphs, and tool integrations.
>- Playbook for designing SaaS and startup products that convert, retain, and monetize — landing pages & CRO, onboarding/activation, churn reduction, pricing psychology, behavioral-science tactics, feature discipline, positioning/ICP, go-to-market, and AI-era differentiation. Use when advising on product design, UX, conversion, landing pages, onboarding, trials, pricing, retention/churn, growth, or positioning for a startup or SaaS. Distilled from product designer Richard (@richardrx). Not for use on gambling, betting, or casino products.
> 偏执型设计顾问 v3.7(融合版)— Jobs 式产品直觉 + Rams 式功能纯粹主义,融合多套顶级设计 Skill 实测精华 (Anthropic frontend-design 的美学胆量、Vercel web-design-guidelines 的工程规范、taste-skill 的反模板拨盘、 Emil Kowalski 的动效工艺、ui-ux-pro-max 的准则化组件行为、IBM Carbon 的组件/模式决策框架)。 重新设计页面、审视 UI 方案、优化交互体验、从零构建界面时使用。 触发词:"重新设计"、"redesign"、"优化界面"、"优化交互"、"设计方案"、"UI 审查"、"这个页面不行"、 "界面不好看"、"帮我看看设计"、"设计建议"、"/design-advisor"。 适用于:(1) 页面/组件设计与重设计 (2) UI/UX 方案评审 (3) 交互逻辑优化 (4) 视觉系统建立 (5) 设计决策咨询 (6) 参考真实网站设计系统 (7) 动效与组件工艺审查。 核心能力:设计读取 + 三拨盘自适应 + 三阶段工作流 + AI 反套路禁令 + Emil 动效工艺套件 + 工程验收清单 + 58 个真实网站的 DESIGN.md 设计系统参考库(Google Stitch 格式)。 额外触发词:"参考XX的设计"、"像XX那样"、"XX风格"、"design system"、"DESIGN.md"、"给我一个设计系统"。
This skill should be used when analyzing business sales and revenue data from CSV files to identify weak areas, generate statistical insights, and provide strategic improvement recommendations. Use when the user requests a business performance report, asks to analyze sales data, wants to identify areas of weakness, or needs recommendations on business improvement strategies.
This skill should be used when the user requests to create professional business documents (proposals, business plans, or budgets) from templates. It provides PDF templates and a Python script for generating filled documents from user data.
This skill should be used when analyzing CSV datasets, handling missing values through intelligent imputation, and creating interactive dashboards to visualize data trends. Use this skill for tasks involving data quality assessment, automated missing value detection and filling, statistical analysis, and generating Plotly Dash dashboards for exploratory data analysis.
This skill should be used when working with CSV files to create interactive data visualizations, generate statistical plots, analyze data distributions, create dashboards, or perform automatic data profiling. It provides comprehensive tools for exploratory data analysis using Plotly for interactive visualizations.
This skill should be used when creating or configuring CI/CD pipeline files for automated testing, building, and deployment. Use this for generating GitHub Actions workflows, GitLab CI configs, CircleCI configs, or other CI/CD platform configurations. Ideal for setting up automated pipelines for Node.js/Next.js applications, including linting, testing, building, and deploying to platforms like Vercel, Netlify, or AWS.
This skill should be used when the user requests brand analysis, brand guidelines creation, brand audits, or establishing brand identity and consistency standards. It provides comprehensive frameworks for analyzing brand elements and creating actionable brand guidelines based on requirements.
This skill should be used when writing documentation for codebases, including README files, architecture documentation, code comments, and API documentation. Use this skill when users request help documenting their code, creating getting-started guides, explaining project structure, or making codebases more accessible to new developers. The skill provides templates, best practices, and structured approaches for creating clear, beginner-friendly documentation.
This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms. Ideal for Next.js, React, Node.js applications requiring containerization for development, production, or CI/CD pipelines. Use this skill when users need Docker configurations, multi-stage builds, container orchestration, or deployment to Kubernetes, ECS, Cloud Run, etc.
This skill should be used whenever users request personal assistance tasks such as schedule management, task tracking, reminder setting, habit monitoring, productivity advice, time management, or any query requiring personalized responses based on user preferences and context. On first use, collects comprehensive user information including schedule, working habits, preferences, goals, and routines. Maintains an intelligent database that automatically organizes and prioritizes information, keeping relevant data and discarding outdated context.
Comprehensive personal finance management system for analyzing transaction data, generating insights, creating visualizations, and providing actionable financial recommendations. Use when users need to analyze spending patterns, track budgets, visualize financial data, extract transactions from PDFs, calculate savings rates, identify spending trends, generate financial reports, or receive personalized budget recommendations. Triggers include requests like "analyze my finances", "track my spending", "create a financial report", "extract transactions from PDF", "visualize my budget", "where is my money going", "financial insights", "spending breakdown", or any finance-related analysis tasks.
This skill should be used whenever users ask food-related questions, meal suggestions, nutrition advice, recipe recommendations, or dietary planning. On first use, the skill collects comprehensive user preferences (allergies, dietary restrictions, goals, likes/dislikes) and stores them in a persistent database. All subsequent food-related responses are personalized based on these stored preferences.
This skill should be used when enhancing the visual design and aesthetics of Next.js web applications. It provides modern UI components, design patterns, color palettes, animations, and layout templates. Use this skill for tasks like improving styling, creating responsive designs, implementing modern UI patterns, adding animations, selecting color schemes, or building aesthetically pleasing frontend interfaces.
Generate professional PowerPoint pitch decks for startups and businesses. Use this skill when users request help creating investor pitch decks, sales presentations, or business pitch presentations. The skill follows standard 10-slide pitch deck structure and includes best practices for content and design.
This skill should be used whenever users need YouTube video scripts written. On first use, collects comprehensive preferences including script type, tone, target audience, style, video length, hook style, use of humor, personality, and storytelling approach. Generates complete, production-ready YouTube scripts tailored to user's specifications for any topic. Maintains database of preferences and past scripts for consistent style.
This skill should be used whenever users need help with resume creation, updating professional profiles, tracking career experiences, managing projects portfolio, or generating tailored resumes for job applications. On first use, extracts data from user's existing resume and maintains a structured database of experiences, projects, education, and skills. Generates professionally styled one-page PDF resumes customized for specific job roles by selecting only the most relevant information from the database.
This skill should be used when the user requests social media content creation for Twitter, Instagram, LinkedIn, or Facebook. It generates platform-optimized posts and saves them in an organized folder structure with meaningful filenames based on event details.
Creates formal academic research papers following IEEE/ACM formatting standards with proper structure, citations, and scholarly writing style. Use when the user asks to write a research paper, academic paper, or conference paper on any topic.
This skill should be used when analyzing HTML/CSS websites for SEO optimization, fixing SEO issues, generating SEO reports, or implementing SEO best practices. Use when the user requests SEO audits, optimization, meta tag improvements, schema markup implementation, sitemap generation, or general search engine optimization tasks.
Answers built from the skills we actually parsed.