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概要と使いどころ
dontbesilent 商业模式诊断。两种模式：问诊（消解你的问题）和体检（拆解你的商业模式）。 触发方式：/dbs-diagnosis、/问诊、「帮我看看商业模式」「诊断一下我的业务」「我有个商业问题」 Business model diagnosis using dontbesilent's ontological framework. Two modes: consultation (dissolve your question) and checkup (analyze your business model). Trigger: /dbs-diagnosis, "diagnose my business model", "I have a business question"
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三个 tab 的团队管理后台: 成员、详情、活动日志, 含图表 + CSV 导出
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Connects Claude Code, Codex, Cursor, and other MCP hosts to Writingmate for model discovery, text comparison, image generation, and video generation with Seedance, Sora, Veo, Kling, PixVerse, and other available models.
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Breaks work into ordered tasks. Use when you have a spec or clear requirements and need to break work into implementable tasks. Use when a task feels too large to start, when you need to estimate scope, or when parallel work is possible.
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。
Scans frontend files for common design system violations using grep-based checks.
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 Mermaid architecture diagrams from your codebase. Produces C4 context and container diagrams, sequence diagrams for key flows, ER diagrams from database schemas, and module dependency graphs. Use when you need architecture diagrams, system diagrams, database ERD, sequence diagrams, dependency visualization, or C4 model diagrams.
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 the current conversation context into a PRD and publish it to the project issue tracker. Use when user wants to create a PRD from the current 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。
Kaggle-first end-to-end competition workflow for scored submissions. Use when Codex must run Kaggle or competitive ML workflows through scored submission, including code competitions, validation, metrics, policy-safe public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling/stacking, proactive multi-notebook architectures, producer notebooks that train models and export private Kaggle artifact datasets, downstream consumer notebooks, Kaggle GPU offload, kagglehub access, hidden-test debugging, and public score retrieval.
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。
Consolidated Galyarder Framework Product intelligence bundle.
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。
Draft and explain persistent goal-loop prompts for long-running agent work with clear stop conditions.
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。
Guides users through a structured interview to clarify their AI agent idea and produces an Agent Requirement Document (ARD).
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。
An almost defiantly minimal documentation-first system that treats the home page like a Markdown README — paper-white canvas, 36px center-aligned heading, a single black pill CTA, an inline terminal install snippet, and a hand-drawn llama mascot as the only ornamental element. No gradient, no hero photography, no marketing pyrotechnics. The chrome is a tiny utility palette of pure black, pure white, and three neutral grays; every interactive element is fully rounded into a pill (`{rounded.full}`); typography is SF Pro Rounded for headings paired with system sans for body and ui-monospace for code. Pricing tiers, FAQs, and "your data stays yours" guarantees all sit on the same flat canvas inside thin-border cards — the system is the documentation, and the documentation is the system.
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Installs and configures ktx, the open-source context layer for data agents — runs ktx setup non-interactively with hidden CLI flags, configures database connections and embeddings, installs agent integration, and verifies readiness. Use when the user asks an agent to add ktx to a project, connect data sources, install agent rules, ingest schema, or troubleshoot a local ktx install.
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Use for writing, reviewing, debugging, or testing Pandera schemas and runtime validation for Polars DataFrame or LazyFrame pipelines installed with pandera[polars]. Trigger on pandera.polars DataFrameSchema, DataFrameModel, Column, Field, Check, PolarsData, decorators, coercion, strictness, lazy error collection, and validation-depth decisions. Do not use for pandas-backed Pandera, Pydantic object models, Polars transformations without Pandera, static dataframe typing alone, or generic data-quality platforms.
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一键发布 agent skill 到 GitHub，自动验证 SKILL.md、生成或检查更吸引人的 README、区分 skill name 与 GitHub repo name、创建或更新仓库、推送并通过 npx skills 真实安装验证。当用户说"发布这个skill"、"publish skill"、"把skill发到GitHub"、"分享这个skill"、"/publish-skill"时触发。支持发布当前目录或指定路径的 skill。
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Use for writing, reviewing, debugging, testing, or optimizing Python code that uses PyArrow arrays, schemas, Tables, RecordBatches, RecordBatchReaders, compute kernels, Dataset scans, Parquet, or Arrow IPC and C data interfaces. Trigger on schema drift, null/type semantics, chunking, batch streaming, predicate projection pushdown, conversion, and memory ownership. Do not use for pandas-only transformations, Polars-only expressions, generic SQL, Arrow Flight service design, C++/Rust Arrow, or Parquet work that does not use PyArrow.
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Identifies reusable UI patterns, components, and design tokens, then extracts and consolidates them into a design system for systematic reuse.
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。
A three-surface marketing system organized around alternating black, white, and PlayStation Blue chapters that scroll past the viewer like a console launch trailer. Each section has a single editorial purpose — hero photography, console product render, PS Plus tier callout, news strip — and each owns one of three full-bleed canvas modes. The chrome is unusually quiet for a gaming brand: bright PlayStation Blue (`#0070d1`) carries every primary CTA as a fully-rounded pill, the proprietary SST face renders display copy at a signature weight 300 (light) for an airy, premium feel, and a crisp 8px-radius secondary card system carries product info on either canvas mode. The system never decorates — no gradient backgrounds on chrome, no atmospheric mesh, no drop shadows beyond a faint section-divide. Imagery does all the heavy lifting: console glamour shots, game key art, and PS Plus tier illustrations occupy 60-90% of every section, with copy compressed into a small editorial slot.
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。
Five-phase pipeline (triage → clarify → research → PRD → plan) that turns a raw idea into four linked files: clarifying questions, deep research, a PRD with non-goals and metrics, and a phased execution plan with mermaid user journey and kill criteria.
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。
Comprehensive autonomous design quality audit across accessibility (WCAG 2.2), performance, theming, responsive/adaptive design, and anti-pattern detection. Produces a prioritized report with severity ratings and fix recommendations. Use when: 'audit design', 'check accessibility', 'a11y audit', 'design review', 'UI quality check', 'WCAG audit', 'design quality'.
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 a Product Requirements Document (PRD) for a new feature. Use when planning a feature, starting a new project, or when asked to create a PRD. Triggers on: create a prd, write prd for, plan this feature, requirements for, spec out.
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。
An inspired interpretation of Shopifi's design language — a cinematic commerce platform that runs two parallel design tracks. The marketing-hero and product-narrative pages live on near-black canvases with full-bleed photography of merchants, giant Neue Haas Grotesk display type at thin weights, and a single black-pill CTA stroked in white. The transactional pages (pricing, signup, dashboards) flip to a cream-mint canvas with pastel aloe and pistachio greens, the same pill button vocabulary, and Inter for UI body. The two tracks share typographic DNA but diverge sharply in canvas polarity — and that choice is the brand.
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。
Identify, categorize, and prioritize accumulated design inconsistencies and structural problems across a product.
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 autonomous design context discovery. Scans the codebase to extract design tokens, typography, colors, spacing, brand patterns, and tech stack, then writes a Design Context section to CLAUDE.md. Zero questions asked. Use when: 'setup design', 'design context', 'design tokens', 'brand discovery', 'design system scan', 'initialize design', 'teach design'.
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。