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38,898 skills indexed with the new KISS metadata standard.
Lightweight playbook distilled from AI Architecture to keep dual-engine memory (.ai_context) and manifest dispatcher with minimal overhead; use when bootstrapping or porting the pattern into Claude Skills format.
Lightweight playbook distilled from AI Architecture to keep dual-engine memory (.ai_context) and manifest dispatcher with minimal overhead; use when bootstrapping or porting the pattern into Claude Skills format.
Lightweight playbook distilled from AI Architecture to keep dual-engine memory (.ai_context) and manifest dispatcher with minimal overhead; use when bootstrapping or porting the pattern into Claude Skills format.
Writing Datasette plugins using Python and the pluggy plugin system. Use when Claude needs to: (1) Create a new Datasette plugin, (2) Implement plugin hooks like prepare_connection, register_routes, render_cell, etc., (3) Add custom SQL functions, (4) Create custom output renderers, (5) Add authentication or permissions logic, (6) Extend Datasette's UI with menus, actions, or templates, (7) Package a plugin for distribution on PyPI
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Share Droid sessions as GitHub gists. Use when asked to "share session", "export session to gist", or "create gist from session".
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Solve context fragmentation across Claude sessions. Use when users mention re-explaining themselves, losing conversation context, starting over, "you forgot," context loss, session continuity, picking up where we left off, or wanting Claude to remember across chats. Also use when users want to create/update their passport, generate session summaries, or maintain project continuity.
Solve context fragmentation across Claude sessions. Use when users mention re-explaining themselves, losing conversation context, starting over, "you forgot," context loss, session continuity, picking up where we left off, or wanting Claude to remember across chats. Also use when users want to create/update their passport, generate session summaries, or maintain project continuity.
Calculate monthly COGS, cost percentages, and manager bonuses (COGS + Top Line) using NET SALES for accuracy and detailed inventory data for restaurant locations.
Solve context fragmentation across Claude sessions. Use when users mention re-explaining themselves, losing conversation context, starting over, "you forgot," context loss, session continuity, picking up where we left off, or wanting Claude to remember across chats. Also use when users want to create/update their passport, generate session summaries, or maintain project continuity.
Expert in email content extraction and analysis. **Use whenever the user mentions .eml files, email messages, says "Extract email information", "Using the email information", or requests to extract, parse, analyze, or process email files.** Handles email thread parsing, attachment extraction, and converting emails to structured markdown format for AI processing. (project, gitignored)
Smart PRD generator with TaskMaster integration. Detects existing PRDs and offers execute/update/replace options. Generates comprehensive technical PRDs optimized for task breakdown, validates with 13 automated checks, and optionally executes tasks autonomously with datetime tracking and rollback support. Use when user requests "PRD", "product requirements", or mentions task-driven development. Default: PRD generation + handoff to TaskMaster. Optional: autonomous execution with 4 modes.
Generate high-quality synthetic datasets using statistical samplers and Claude's native LLM capabilities. Use when users ask to create synthetic data, generate datasets, create fake/mock data, generate test data, training data, or any data generation task. Supports CSV, JSON, JSONL, Parquet output. Adapted from NVIDIA NeMo DataDesigner (Apache 2.0).
Refactor HTML/TSX files to use existing UI components, DaisyUI classes, and semantic colors. Use when (1) refactoring React/TSX page components to use reusable UI components, (2) replacing raw HTML elements with component library equivalents, (3) converting primitive Tailwind colors to semantic DaisyUI colors, (4) extracting repeated styling patterns into components.
Generate high-quality synthetic datasets using statistical samplers and Claude's native LLM capabilities. Use when users ask to create synthetic data, generate datasets, create fake/mock data, generate test data, training data, or any data generation task. Supports CSV, JSON, JSONL, Parquet output. Adapted from NVIDIA NeMo DataDesigner (Apache 2.0).
Memory preservation for Claude Code sessions. Use when approaching token limits, needing to /reset or /compact, switching between complex tasks, or preserving critical session state before context loss. Creates comprehensive memory dumps at /tmp/total-recall containing current state, decisions, artifacts, and next steps for seamless context restoration.
Detects and corrects Korean AI writing patterns to transform text into natural human writing. Based on scientific linguistic research (KatFishNet paper with 94.88% AUC accuracy). Analyzes 19 patterns including comma overuse, spacing rigidity, POS diversity, AI vocabulary overuse, and structural monotony. Use when humanizing Korean text from ChatGPT/Claude/Gemini or removing AI traces from Korean LLM output.
Detects and corrects Korean AI writing patterns to transform text into natural human writing. Based on scientific linguistic research (KatFishNet paper with 94.88% AUC accuracy). Analyzes 19 patterns including comma overuse, spacing rigidity, POS diversity, AI vocabulary overuse, and structural monotony. Use when humanizing Korean text from ChatGPT/Claude/Gemini or removing AI traces from Korean LLM output.
Use this skill when the user needs to analyze, clean, or prepare datasets. Helps with listing columns, detecting data types (text, categorical, ordinal, numeric), identifying data quality issues, and cleaning values that don't fit expected patterns. Invoke when users mention data cleaning, data quality, column analysis, type detection, or preparing datasets.
Detects and corrects Korean AI writing patterns to transform text into natural human writing. Based on scientific linguistic research (KatFishNet paper with 94.88% AUC accuracy). Analyzes 19 patterns including comma overuse, spacing rigidity, POS diversity, AI vocabulary overuse, and structural monotony. Use when humanizing Korean text from ChatGPT/Claude/Gemini or removing AI traces from Korean LLM output.
2. 算法 链表翻转 异或取数组中的不同数
Interface with Zotero's MCP server to search and retrieve bibliographic data using advanced semantic search and multi-strategy approaches. Designed for output as a plain markdown formatted outline, suitable for pasting into Logseq. Also offers side-by-side translation of Chinese titles and abstracts for improved English language search within Logseq. Context-aware - uses agents in Claude Code, batched searches in Claude Desktop.