「output style」の検索結果

Create premium hand-drawn architecture, workflow, and swimlane diagrams in a dark neon or light paper style, with editable Excalidraw sources, PNG/SVG previews, animated GIF/MP4 output, and interactive HTML. Use whenever the user asks for 岚叔动态架构图、手绘架构图、Excalidraw 风格图、DailyDoseOfDS 风格技术图、动态流程图、泳道图、系统可视化，或希望复刻并提升参考架构图。

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。

Cowork-style sweep of a folder of receipts, statements, and expense exports -- categorizes every transaction, matches receipts to statement lines, flags policy violations and anomalies, and outputs a clean expense report plus a findings memo.

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。

Uses Cowork-style multi-step analysis to process deal room documents -- contracts, financials, org charts. Outputs risk assessment, term comparison, key findings, and negotiation recommendations.

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 should be used when the user asks to "validate", "reindex", "repair registries", "check links", "run the continuity, pacing, clue, voice, or name checks", "count words", "summarize a story project", "import an existing manuscript", "export a manuscript", "run a build", "generate a diagram", "record revision-pass status with `story passes`", "run the story CLI", or wants deterministic maintenance on a Story Skills markdown project. It runs the CLI and reads its output; NOT for judging a finding or revising the story to fix it (use revision-continuity for continuity errors and revision passes, plot-structure for pacing, voice-style for voices and prose, genre-craft for clues and fair play), or for sharing a review copy with readers (use feedback-triage).

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。

Fix git pre-commit hook failures in Flutter projects when using git worktrees. Use when: (1) Pre-commit hook with `flutter analyze` fails during `git commit` but passes when run manually, (2) Hook output shows "Resolving dependencies..." then immediately fails with no actual analysis errors, (3) Working in a git worktree (created via `git worktree add`). Root cause: git sets GIT_DIR to a worktree-style path during hook execution, which breaks `flutter pub get` (called internally by `flutter analyze`). Fix: unset GIT_DIR, GIT_INDEX_FILE, and GIT_WORK_TREE before flutter/dart commands in the hook.

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。

Convert FIRE analysis cards, Chinese knowledge notes, or project-note JSON into validated EPUB books with directory cards, chapter cards, keyword index cards, backlinks, and GitHub-shareable ebook assets. Use when Codex needs to teach or automate the path from `fire-analysis-card` outputs to `project-note-json-to-epub` style EPUB files, including sample JSON manuscripts and attached `.epub` deliverables.

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。

Assign, validate, normalize, and explain Luhmann/Zettelkasten-style project-note codes for Chinese book manuscripts, Obsidian Markdown folders, Mandala-Grid section files, HyperCard Markdown stacks, and project-note JSON to EPUB workflows. Use when Codex needs to scan folders for 部/章/節/項/目 numbering, generate stable card ids, insert branch codes without renumbering existing notes, map letter-coded branches to Obsidian Mandala sections, preserve K### keyword index cards, sanitize private catalogs into public examples, or prepare card IDs for EPUB and HyperCard output.

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。

Transforms natural language requirements (user stories, verbal descriptions, business rules) into formal specifications and constraints. Use when converting informal requirements into structured, testable specifications with explicit constraints. Outputs in multiple formats including BDD-style Given-When-Then, JSON Schema, and structured plain text requirements documents.

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。

Social Media Publisher. Takes approved content from outputs/ and schedules it across platforms via Blotato MCP. Generates infographic-style visuals (stat cards, framework diagrams, process graphics, quote graphics) for posts flagged by platform-specialist skills. Requires Blotato MCP to be configured. Run after /linkedin-writer, /threads-writer, /x-writer, or /caption-writer.

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。

Read, edit, redline, comment on, and create Microsoft Word .docx files. Use to fill out or edit a Word doc, redline a contract with tracked changes, add/resolve comments, replace text keeping its formatting, restyle headings/fonts, edit tables, or read/extract a .docx as Markdown or text. Also BUILD a new .docx — from Markdown or programmatically (code that outputs a Word report with headings, tables, images). Not for PDF, Google Docs, Excel, PowerPoint, or .doc.

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。

One-time setup for absolute: interview how you want it to behave (output style, autonomy, TDD strictness, spec dir, families) + detect the stack once, then write `.absolute.config.json` (project, committed) and `~/.absolute/config.json` (user defaults + per-project overrides). Every other absolute-* command reads it instead of re-detecting; non-blocking — commands proceed without it and soft-recommend it. Triggers on "absolute init", "set up absolute", "initialize absolute", "configure absolute", "first-time setup", "remember my conventions for this repo".

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。

Learn reusable 2D motion-generation knowledge from user-specified action resources with `/img2mo-learn <resource>`. Use when the user provides videos, extracted frame sequences, spritesheets, Spine assets, generated outputs, failed attempts, or reference motion folders and wants to summarize animation timing, pose beats, style traits, prompt patterns, extraction/cropping rules, or failure lessons into the project `img2mo-knowledge/` folder for later `/img2motion` generation.

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。

Internal speech module for /codeck. Reads deck content, asks about style and duration only when missing, generates a verbatim speech transcript with stage directions. Outputs $DECK_DIR/speech.md.

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 the changelog as a distribution surface bridging engineering releases (DEP-/FEA-) to marketing channels (GTM-) during PRD v0.8 Deployment & Ops. Triggers on requests to set up a changelog system, publish releases, or when user asks "how should we publish releases?", "changelog as marketing", "release notes", "Stripe-style changelog", "what to do with our release notes", "ship and tell". Outputs MON-CHG-* changelog entries and per-channel 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。

Create dark-themed, animated technical diagrams as self-contained HTML+SVG files — flowcharts whose connectors visibly flow, and architecture diagrams where requests travel as light dots through the system (Diagrid/Temporal landing-page style). Use this skill whenever the user asks for a flowchart, workflow, pipeline, process diagram, state machine, system architecture, infrastructure, cloud, microservices, or network topology diagram — and especially when they mention "animated", "flowing", "dynamic", "alive", "GIF-like", or want a diagram for a landing page, README, docs, or product demo. Also use it to convert Mermaid source (a mermaid code block or .mmd file) into an animated diagram — "animate this mermaid", "make this flowchart move". Prefer this over static diagram output whenever the diagram represents anything that moves: requests, events, data, jobs, messages, or control flow.

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。

Generate Word documents programmatically with the docx library — create paragraphs, tables, images, headers, footers, numbered lists, and styled content. Use when tasks involve generating contracts, proposals, resumes, or any .docx output from application data in Node.js.

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。

The enhancement layer for AI-generated content. This skill covers AI-powered visual effects, compositing, upscaling, restoration, and post-production magic—turning raw AI output into polished, professional content. AI generation gets you 80% of the way. Visual effects get you the remaining 20% that separates "clearly AI" from "how did they do that?" This skill covers ComfyUI workflows, Runway's AI tools, intelligent upscaling, rotoscoping, color grading, and the integration of AI elements into traditional footage. The practitioners of this skill are technical artists who understand both traditional VFX workflows and the new AI-native approaches that are revolutionizing post-production. Use when "AI visual effects, VFX, upscale, upscaling, composite, rotoscope, background removal, color grade, inpaint, outpaint, style transfer, enhance, ComfyUI, post-production AI, vfx, visual-effects, compositing, upscaling, post-production, comfyui, enhancement, color-grading" mentioned.

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。

Extract brand identity from a website URL — voice, colors, typography, imagery, values, and target audience — into a structured brand-profile.json. The profile feeds downstream skills (seo-content-writer, email-composer, frontend-design, pro-deck-builder, cross-platform-audit) for brand-consistent output. Use when the user says brand DNA, brand profile, extract brand, analyze brand, brand voice, brand identity, brand colors, or brand style guide.

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。

Analyze images, websites, and Figma files to extract their design and generate a `design.md` with token system, component inventory, and reconstruction notes. Use this skill whenever the user wants to understand, document, replicate, or audit the design of something visual: a screenshot, a URL, a Figma link, a Pinterest reference, a mockup, a competitor's site, a component, a dashboard, a landing page. Also when they ask 'extract the design system from X', 'document the style of Y', 'analyze this visually', 'convert this image into tokens', 'help me replicate this design', 'what palette does this site use', 'how is this built'. Also for single elements: 'copy this navbar', 'recreate this illustration', 'give me a prompt to regenerate this graphic' — element mode outputs a focused element.md, with token-grounded image-model prompts when the element is visual art. If the user brings any visual source and wants to understand it at a design level — this skill should activate.

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 a 3-month SEO performance HTML report for any domain using DataForSEO data. Fetches baseline vs current traffic, keyword rankings, top content pages, and competitive landscape, then outputs a report styled with the Infrasity brand design system: #0D0A1A background, #8157F2 purple accent, Instrument Sans + DM Sans + DM Mono typography. Use this skill whenever a user provides a target domain and a list of competitor URLs and asks for an SEO report, performance report, SEO analysis, competitive SEO comparison, traffic report, ranking report, or 3-month SEO summary. Also trigger when the user says "generate SEO report for X vs Y and Z", "create a performance report", "compare my SEO against competitors", or pastes a domain and asks how it's performing versus the market. Always use this skill for SEO report generation — do not attempt to build the report without following this structured data-fetch and HTML generation workflow.

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。

Builds end-to-end predictive modeling pipelines on tabular datasets—data exploration, preprocessing, baseline modeling, and mandatory optimization—producing valid saved predictions in the required output format. Use for any supervised machine learning or data modeling task, including classification and regression on tabular data, Kaggle-style competitions or submission-file challenges, training a model to predict a target from features, or requests to fit/tune/evaluate models with scikit-learn, XGBoost, Random Forest, Logistic Regression, and similar non-deep-learning methods. Runs fully automated end-to-end without asking the user for intermediate decisions.

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。

Generate professional diagrams as valid draw.io XML — flowcharts, architecture, C4 models, ER diagrams, sequence diagrams, mind maps, and swimlanes. Don't use for Excalidraw or Mermaid output, hand-drawn sketch styles, or slide decks/presentations.

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。

Analyze images, websites, and Figma files to extract their design and generate a `design.md` with token system, component inventory, and reconstruction notes. Use this skill whenever the user wants to understand, document, replicate, or audit the design of something visual: a screenshot, a URL, a Figma link, a Pinterest reference, a mockup, a competitor's site, a component, a dashboard, a landing page. Also when they ask 'extract the design system from X', 'document the style of Y', 'analyze this visually', 'convert this image into tokens', 'help me replicate this design', 'what palette does this site use', 'how is this built'. Also for single elements: 'copy this navbar', 'recreate this illustration', 'give me a prompt to regenerate this graphic' — element mode outputs a focused element.md, with token-grounded image-model prompts when the element is visual art. If the user brings any visual source and wants to understand it at a design level — this skill should activate.

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。

Lightweight, script-driven variant of data2motion for turning data into a smooth, on-brand animated chart (one self-contained HTML) — built for a TEXT-ONLY model that cannot see its own output. You never write HTML/CSS/SVG/animation; you extract the data, pick a chart, fill a small JSON spec, and run one build script that owns 100% of the look and the motion, so the result cannot drift from the house template style or lose its smoothness. Use to turn a number/stat/table/CSV/paragraph into a quick animated chart, data reveal, or KPI when you want guaranteed template fidelity with minimal reasoning and no image feedback.

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。