Results for “wan”

MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.

Expert content repurposing skill for creators and professionals who want to get more out of content they've already created. Use this skill whenever the user wants to turn one piece of content into multiple formats — for example: turning a blog post into social media posts, converting a YouTube video or podcast into a newsletter or article, transforming a long-form piece into short clips or quotes, or adapting any content for a different platform or audience. Triggers: "repurpose this", "turn this into a post", "make a LinkedIn post from this", "convert this blog to a tweet thread", "I have a video/podcast, can you make it into a newsletter", "get more out of this content", "adapt this for [platform]", or any request to transform existing content into a new format. Do NOT limit to obvious repurposing requests — if the user shares content and mentions another platform or format, use this skill.

Build Simulink models that co-simulate with Eclipse SUMO traffic simulator. Use when creating SUMO-Simulink co-simulation, traffic simulation, TraCI connection, vehicle-in-the-loop testing, or ADAS scenario validation with SUMO. Covers Server/Client setup, Reader/Writer/Actor block configuration, random traffic generation, ego vehicle control, and SUMO file creation. Also use when the user mentions SumoInterfaceLibrary, .sumocfg files, or wants to connect Simulink to an external traffic simulator.

Use when creating new Excalidraw diagrams or reading, modifying, or comparing existing .excalidraw or .excalidraw.json files. Also use when the user asks for hand-drawn style diagrams, whiteboard sketches, architecture diagrams in Excalidraw format, or wants to export Excalidraw to SVG/PNG. Use this skill even if the user doesn't say "Excalidraw" — for example when they ask for a system diagram, flowchart, or architecture sketch that should look hand-drawn or informal.

Put the user in the hot seat — one question at a time until their plan, decision, or idea actually holds up. Use whenever the user says "hot seat me", "grill me", "stress-test this", "poke holes in this", "am I missing anything", or drops a plan and wants it challenged before anyone acts on it — even if they never say the words. Also used as a sub-procedure by the whiteboard and connotation-cop skills.

Run a full pull request review and post review comments directly to the current branch's GitHub PR. Requires the gh CLI to be installed and a PR to already exist for the current branch. Use when you want review feedback posted to GitHub as PR comments. For local code review without posting to GitHub, use code-review instead. Does not write or update PR descriptions — use update-pr-description for that.

Fix Robin Image Optimizer — installs plugin if missing, configures optimal settings, unsticks the bulk optimization loop, generates missing .webp files locally, and syncs the queue database so the plugin recognizes all conversions. Use when the user says Robin Optimizer is stuck, frozen, looping, not finishing, missing webp files, needs setup, or wants to install and configure it properly. Also use for "optimize all images", "configure image optimizer", or when Robin shows "X remaining" but never completes.

Runs a Tinder-style swipe interview to pull requirements out of someone's head. Claude generates a deep pool of question cards, the user swipes right/left/up/down (yes / no / absolutely / not sure), the deck reshapes itself around every swipe, and it ends in a written brief once a saturation meter fills. Use this whenever a request is vague, broad, or taste-dependent and you would otherwise fire off a list of clarifying questions — kicking off a project, scoping a build, planning a trip or event, choosing a direction, naming something, deciding what to eat, or any "help me figure out what I want". Trigger on "swipe", "swipe deck", "tinder style", "interview me", "ask me questions", "quiz me", "20 questions me", "figure out what I want", "get it out of my head". Also reach for it proactively any time you catch yourself about to ask more than three clarifying questions in a row, or when someone says a batch of questions felt like a chore or a form.

Launch a fixed-supply V3 token on Robinhood Chain (4663) via PonsLaunchFactory (pons.family), reverse-discover the factory from live PonsLauncherToken tokens, prepare launchToken txs, and verify TokenLaunched receipts. Use when the user says "launch on Pons", "pons.family launch", "PonsLaunchFactory", "launchToken", "PonsLauncherToken", "V3 launch on Robinhood", or wants agents to create a Pons token. Does NOT use RH bonding-curve createToken (rh-bonded-launch), does NOT mint Solana $CLAWD, and does NOT use NOXA Fun factories.

Build throwaway code that answers exactly one design question — a tiny terminal app to feel out logic/state models, or several radically different UI variants switchable on one route. Use when the user wants to "prototype", "mock up", "sketch", "try a few versions", "see what it'd look like", "feel out this state machine", or is stuck choosing between designs they can only judge by seeing or driving them. Also used by the whiteboard skill for napkin-type tickets.

Police the project's vocabulary — bust vague terms, keep the CONTEXT.md glossary sharp, and lock in decisions worth remembering as ADRs. Use when the user debates naming, says "what should we call this", asks to pin down terminology, wants a decision recorded, or when another skill (hot-seat, whiteboard) surfaces a decision that clears the ADR bar. Just reading the glossary for vocabulary is NOT this skill — trigger only when the words or decisions are being changed.

Simulator.Company form designer specialist. Use when the user wants to create or modify form templates (a.k.a. Account Templates / «Шаблон рахунків»), define custom field structures, set up account definitions, explore system forms, work with Smart Forms (CDU / Scripts), manage form status, or understand how forms define actor structure. Activate when the user says "create a form", "design a template", "add fields to form", "Account Template", "Шаблон рахунків", "define actor schema", or "what system forms are available".

Use when the user wants to use the UCP CLI to find, compare, buy, or track products from online merchants, or to set up and troubleshoot the local UCP profile required for merchant-scoped operations. Covers global catalog search ("find me X under $Y"), named-merchant transactions ("buy this from Z.com"), order tracking, `ucp profile init`, `ucp doctor`, carts, checkout, orders, and UCP setup/help. Falls back to merchant-hosted handoff when direct in-protocol checkout isn't available.

Simulator.Company files & attachments specialist. Use when the user wants to upload a file, attach a document/image to an actor or comment, list/rename/detach workspace files. Activate when the user says "upload a file", "attach this document", "add an attachment", "rename the file", "detach the file", "list workspace files", "завантаж файл", "прикріпи файл/документ", "відкріпи вкладення", "загрузи файл", "прикрепи документ". For setting an actor's picture/avatar use the `uploadActorPicture` engine tool; for comments that carry files use `simulator-reactions`.

Pythinker WebBridge lets AI control the user's real browser — navigate, click, type, read, screenshot, and interact with any website using the user's actual login sessions. Use this skill whenever the user wants to interact with websites, automate browser tasks, scrape web content, or perform any action requiring a real browser. Also use when the user mentions "browser", "webpage", "open URL", "screenshot", or asks to read/interact with any website. Use even for simple-sounding browser requests — the daemon handles all complexity.

Build a compact, validation-gated implementation plan for multi-step, risky, or ambiguous work — typically when phases need explicit checkpoints, the change touches multiple files/services, or the user wants alignment before execution. Output goes to `.claude/plans/<topic>.md` (or `.agents/plans/`) with goal, in/out-of-scope, phased steps, validation per phase, and replanning triggers. Skip for trivial single-file fixes, bug investigations (use `tracer`), or open-ended exploration (use `explore`). Pair with `ship` once the plan ends and merge work begins.

Use for PUA/try-harder productivity coaching when the user expresses frustration, repeated failure, quality complaint, passive behavior, says retry/change approach/don't give up, asks for evidence/completion check/test before done, or wants Ding-style workplace reminders. Triggers include: try harder, stop giving up, figure it out, again??, why still failing, change approach, no evidence, run tests, done without proof, 换个方法, 再试试, 别摆烂, 别偷懒, 为什么还不行, 又错了, 证据呢, 没跑测试别说完成, 验收, 闭环, 自嗨, 置身钉外, 无招, 老板体感. Do not use for calm first-attempt requests.

Use for PUA/try-harder productivity coaching when the user expresses frustration, repeated failure, quality complaint, passive behavior, says retry/change approach/don't give up, asks for evidence/completion check/test before done, or wants Ding-style workplace reminders. Triggers include: try harder, stop giving up, figure it out, again??, why still failing, change approach, no evidence, run tests, done without proof, 换个方法, 再试试, 别摆烂, 别偷懒, 为什么还不行, 又错了, 证据呢, 没跑测试别说完成, 验收, 闭环, 自嗨, 置身钉外, 无招, 老板体感. Do not use for calm first-attempt requests.

Interactive project learning coach via interview-style Q&A. Reads codebase and docs, dynamically generates interview questions per knowledge domain and sub-topic, conducts up to 4 follow-up rounds, scores answers, provides learning guidance with code/doc references, and persists progress. 10 domains × 3-5 sub-topics = 45 knowledge points for comprehensive interview coverage. Use when user says '学习项目', '了解项目', '检验项目', '项目学习', '面试准备', 'learn project', 'study project', 'review project', 'interview prep', 'knowledge check', or wants to understand/master the project through guided Q&A.

Interactive project learning coach via interview-style Q&A. Reads codebase and docs, dynamically generates interview questions per knowledge domain and sub-topic, conducts up to 4 follow-up rounds, scores answers, provides learning guidance with code/doc references, and persists progress. 10 domains × 3-5 sub-topics = 45 knowledge points for comprehensive interview coverage. Use when user says '学习项目', '了解项目', '检验项目', '项目学习', '面试准备', 'learn project', 'study project', 'review project', 'interview prep', 'knowledge check', or wants to understand/master the project through guided Q&A.

Read BEFORE troubleshooting or enhancing camera image quality. Diagnoses and enhances image quality from cameras connected via Image Acquisition Toolbox or USB Webcams support package. Discovers camera capabilities at runtime, analyzes captured images for quality issues (brightness, contrast, sharpness, noise, color balance, backlighting), suggests hardware setting adjustments tailored to the specific camera, and applies Image Processing Toolbox enhancement functions. Use when a user wants to improve camera image quality, troubleshoot dark/blurry/noisy/grainy/ overexposed/washed out/color cast images, or optimize camera settings.

Kimi WebBridge lets AI control the user's real browser — navigate, click, type, read, screenshot, and interact with any website using the user's actual login sessions. Use this skill whenever the user wants to interact with websites, automate browser tasks, scrape web content, or perform any action requiring a real browser. Also use when the user mentions "browser", "webpage", "open URL", "screenshot", or asks to read/interact with any website. Use even for simple-sounding browser requests — the daemon handles all complexity.

Connect to and acquire images from cameras in MATLAB using Image Acquisition Toolbox. Use this skill when the user wants to: use a webcam, acquire images, capture video, stream from a camera, connect to a GigE Vision camera, preview live video, list available cameras, configure camera properties, use a CoaXPress frame grabber, or use a Camera Link frame grabber. Covers USB webcams, GigE Vision, USB3 Vision, CoaXPress, Camera Link, and GenICam-compliant cameras. Always prefer videoinput from Image Acquisition Toolbox over webcam support package or gigecam.

Walk into the negotiation with a plan, not a hope. Sets your walk-away and your target, builds the concession ladder (what you trade and what you get for it), maps their likely asks, and drafts the responses that protect price and terms. Built for B2B sales teams, customizable to your CRM and your deal process. Trigger on "prep me for this negotiation", "the prospect wants a discount", "what should I concede", "build my concession ladder", "hold price on a new deal", or any pre-negotiation planning.

Self-contained code review checklist — formatting, type safety, duplication, readable conditions, logic-out-of-UI, test coverage, comment quality. Adapts to whatever tooling the project actually has (skips Prettier/TypeScript/test-runner checks if unconfigured). Use before merging, after completing a feature, or any time you want a second pass on code quality. In Claude Code, prefer the official `code-review` skill or `pr-review-toolkit`/`feature-dev` code-reviewer agents instead — both are real, installed, and go deeper than this checklist. This copy exists for Codex/Cursor portability, where those agents aren't available.

Break a work-items.md file (produced by /plan-work-items) into independently-grabbable GitHub issues, one per slice, in each slice's target repo. Use when you want to turn a work-items file into GitHub issues, publish work items as issue tickets, or create implementation tickets that can be worked on and tracked on GitHub. Does not produce the work-items file itself — use plan-work-items to break a plan into work items first. Does not review code or post pull request comments — use post-code-review-to-pr for that.

Run a pre-mortem — imagine the project has already failed one year from now and work backward to find the root causes before they happen. Load when the user asks for a pre-mortem, wants to imagine failure before committing, asks "what could go wrong before we start", "assume this fails — why", "risk analysis before launch", "what kills this project", "what could go wrong", or when deep-thinking diagnoses a pre-mortem frame. Based on Gary Klein's prospective hindsight method, which surfaces failure causes more effectively than forward risk analysis. Most useful right before a major commitment.

Simulator.Company reactions specialist — comments, events, approvals, ratings and other feedback attached under an actor. Use when the user wants to comment on an actor, reply in a thread, read/like/pin the discussion, mark comments read, or get reaction stats. Activate when the user says "comment on this actor", "leave a note", "reply to", "show the comments/discussion", "pin this comment", "mark as read", "прокоментуй актор", "залиш коментар", "відповісти на коментар", "закріпи коментар", "оставь комментарий", "ответь в треде", "закрепи комментарий". For attaching FILES to a reaction use `simulator-attachments`; for the actor's own fields use `simulator-actors`.

Systematic writing framework for philosophy and interdisciplinary academic papers from optimized outline to submission-ready manuscript. Use when users want to: (1) write a paper from a detailed outline, (2) ensure quality control during writing, (3) maintain consistency across chapters, (4) prepare a submission-ready manuscript, or (5) systematically execute a planned paper. Triggered by phrases like 'write the paper from this outline,' 'compose the full manuscript,' 'execute the outline,' or when users have completed strategic planning (academic-paper-strategist skill) and are ready to write. Takes optimized outline as input; outputs complete manuscript with iterative quality checks.

Simulator.Company chart and dashboard specialist. Use when the user wants to create, configure, or query charts (line, bar, area), dashboards, or financial time-series visualisations on a graph layer. Trigger on any of these intents: — Creating: "create chart", "add chart", "create dashboard", "add dashboard", "build visualisation", "chart на графе", "график с данными", "дашборд", "show metrics on graph", "visualise account data", "plot actor balances". — Configuring: "change chart type", "switch to bar chart", "update chart range", "use last day", "show turnover", "change time range", "filter chart actors". — Querying: "get chart data", "show dashboard", "what charts are on this layer", "fetch chart metrics", "dashboard data".

Splits a body of context into a sequence of vertical-slice build phases where each phase is independently demonstrable to a real user and each builds on the previous. Use when the user wants to plan, sequence, phase, slice, break down, or order the build of a feature, capability, system, or initiative, and produces a plain-language phased build outline. Does not produce implementation detail — use plan-implementation. Does not specify behavior that has not been decided — use plan-a-feature. Does not perform gap analysis between two artifacts — use gap-analysis. Does not break a plan into independently-grabbable work items — use plan-work-items.

Turn a rough idea into a fully approved design before any code is written. Load when the user wants to brainstorm, explore ideas, design a feature, think through approaches, plan a new capability, or figure out what to build. Also triggers on "let's think through", "help me design", "explore options", "what's the best approach for", "I have an idea for", "before we build", or any request to design something before implementation. Enforces a hard gate: no code, no implementation until user approves a design. For executable feature specs (FRs, NFRs, ACs as Given/When/Then), route to `feature-spec` instead — brainstorming owns approach and architecture, not machine-readable requirements.

Sharpens and stress-tests an existing plan file through multiple codebase-grounded review passes, editing it in place and recording every finding and iteration in cross-referenced companion files. Use this skill whenever the user wants to iterate on, refine, tighten, or improve a plan. Also use it when the user asks to verify, validate, or confirm feasibility of an approach. Does not implement plan steps, write test plans, review code, or investigate bugs, and does not generate new plans from scratch — use plan-a-feature for a new plan. Runs its review rounds to completion without pausing between them; to review each round as it lands, use pairing.

Analyze and optimize X (Twitter) posts for viral potential and reach using heuristics inspired by X's published open-source recommendation architecture. Use when user wants to: (1) Check if a post will go viral, (2) Score a tweet for engagement potential, (3) Optimize or rewrite a tweet for algorithmic reach, (4) Understand why a tweet underperformed, (5) Build audience in a specific niche. Triggers: "Check if this will go viral", "Make this post buzz", "Will this tweet perform well?", "Optimize my tweet", "How can I make this viral?", "rewrite this tweet", "improve my tweet engagement", "twitter algorithm", "tweet reach", "debug underperforming tweet", "バズるかチェックして", "Xでバズる投稿にして", "伸びるかチェックして", "この投稿を伸ばして", "投稿を改善して", "ツイートを最適化して"

Remove AI writing patterns from prose. Use this skill when writing, drafting, editing, reviewing, or revising any text to eliminate predictable AI tells, slop, and formulaic patterns. Trigger this skill whenever the user asks to "deslop", "de-AI", "make it sound human," "remove AI patterns," "remove AI tropes," "clean up AI writing," fix "slop," "deslop" text, or review prose for authenticity. Also use when the user asks you to write or draft anything and wants it to sound natural rather than AI-generated. Common use cases include scientific writing (manuscripts, abstracts, cover letters, grant narratives, discussion sections, peer review responses), blog posts, newsletters, memos, reports, and any other substantial prose.

Pose-conditioned generation on RunComfy via the `runcomfy` CLI. Routes across Kling 2-6 Motion Control Pro / Standard (transfer the motion / blocking of a reference video onto a target character), community Wan 2-2 Animate (audio-driven character animation with pose conditioning), and Z-Image Turbo ControlNet LoRA (pose-conditioned image generation from an OpenPose / DWPose / canny / depth control image). Picks the right route based on video vs still and stylized vs photoreal. Triggers on "controlnet", "control net", "pose control", "openpose", "DWPose", "transfer pose", "motion control", "pose driven", "character pose", "depth control", "canny edge", "use this pose", or any explicit ask to condition generation on a pose / skeleton / motion / depth / canny reference.