腳本程式

This skill should be used when the user asks to "generate gitlab-ci.yml", "create GitLab CI pipeline", "configure GitLab CI/CD", "use To-Be-Continuous templates", "setup TBC templates", "create CI/CD for Python/Node/Go/Java project", "configure Docker build in GitLab", "setup Kubernetes deployment in GitLab", "add SonarQube to GitLab CI", "configure Terraform with GitLab", or mentions "TBC", "To-Be-Continuous", "Kicker", or needs help selecting CI/CD templates for their project.

Python and R programming for data analysis, automation, and reproducible analytics

Implement secure authentication and authorization using Clerk. Use this skill when you need to authenticate users, protect routes, check permissions, implement subscription-based access control, or integrate Clerk with your application. Triggers include "authentication", "auth", "authorization", "Clerk", "protect route", "check user", "sign in", "session", "permissions", "subscription access".

This skill should be used when implementing, debugging, or discussing WebSocket connections for Nostr relays. Provides comprehensive knowledge of RFC 6455 WebSocket protocol, production-ready implementation patterns in Go (khatru), C++ (strfry), and Rust (nostr-rs-relay), including connection lifecycle, message framing, subscription management, and performance optimization techniques specific to Nostr relay operations.

Use this skill when creating or refining Claude Code hooks. Hooks are shell commands that execute at specific lifecycle events (tool use, prompt submit, notifications, session events). Helps design event handlers for notifications, formatting, logging, feedback, and permission control. Automatically invoked when user requests "create a hook", "add automation", "event handler", "workflow automation", or mentions hook development.

Create GitHub pull request with atomic Beads issue closure. MUST BE USED for opening PRs.Asks if work is complete - if YES, closes Beads issue BEFORE creating PR (JSONL merges atomically with code).If NO, creates draft PR with issue still open. Automatically links Beads tracking and includes Feature-Key.Use when user wants to open a PR, submit work for review, merge into master, or prepare for deployment,or when user mentions "ready for review", "create PR", "open PR", "merge conflicts", "CI checks needed","branch ahead of master", PR creation, opening pull requests, deployment preparation, or submitting for team review.

專責處理 IDF (Information Display Frame) 類型的需求。讀取規格目錄結構，生成/審查 Query Side 設計與實作。支援 Java、TypeScript、Go 多語言。

Identify decision-maker contacts at target companies using web research for LinkedIn queries, email patterns, and phone research methods based on ICP buyer personas. Use when you need to find contacts at qualified prospects.

Create SEMO slash commands following Claude Code conventions. Use when (1) need to add new /SEMO:command, (2) creating interactive workflows triggered by slash commands, (3) packaging command-based operations.

Expert system for designing, structuring, and optimizing Cursor Rules (.cursor/rules/*.md). Use this skill when you need to create new rules, update existing ones, or design a hierarchical rule system for a project to improve AI code generation and workflow automation.

Investigates HEC-HMS internals through decompiled Java classes. Provides JythonHmsAPI reference, CLI options, version-specific differences (3.x vs 4.x), and guideson-demand decompilation for new discoveries. Use when debugging HMS behavior,discovering undocumented features, understanding version differences, validatingautomation approaches, or investigating HMS API capabilities. Includes completeJythonHms method reference, Python 2 vs 3 syntax differences, and decompilationtooling. Complements hms_doc_query (official docs) with internal implementation details.Trigger keywords: decompile, HMS internals, JythonHms API, HMS version differences,CLI options, undocumented, HMS jar, HMS classes, debugging HMS, HMS source code,HMS 3.x support, Python 2 vs 3, HMS methods, HMS parameters.

Expert knowledge on Stripe integration, subscription plans (Glow Up, Viral Surge, Fame Flex), trial logic, plan enforcement, webhooks, and billing synchronization. Use this skill when user asks about "subscription", "billing", "stripe", "payment", "plan limits", "trial", "upgrade", "downgrade", "webhook", or "plan enforcement".

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.

Expert at analyzing the quality and effectiveness of Claude Code components (agents, skills, commands, hooks). Assumes component is already technically valid. Evaluates description clarity, tool permissions, auto-invoke triggers, security, and usability to provide quality scores and improvement suggestions.

Implement structured logging with context, log levels, log aggregation. Python logging, Winston, Pino. JSON logs for production. Keywords - structured logging, json logs, winston, pino, python logging, log aggregation, contextual logging

This skill should be used when the user asks to "create a plot", "make a chart", "visualize data", "create a heatmap", "make a scatter plot", "plot time series", "create publication figures", "customize plot styling", "use matplotlib", "use seaborn", or needs guidance on Python data visualization, statistical graphics, or figure export.

Native Fabric pattern execution for Claude Code. USE WHEN processing content with Fabric patterns (extract_wisdom, summarize, analyze_claims, threat modeling, etc.). Patterns run natively in Claude's context - no CLI spawning needed. Only use fabric CLI for YouTube transcripts (-y) or pattern updates (-U).

Master ESLint, Prettier, TypeScript, and pre-commit hooks for code quality enforcement.

Master protocol for deconstructing agent frameworks to inform derivative system architecture. Use when (1) analyzing an agent framework's codebase comprehensively, (2) comparing multiple frameworks to select best practices, (3) designing a new agent system based on prior art, (4) documenting architectural decisions with evidence, or (5) conducting technical due diligence on AI agent implementations. This skill orchestrates sub-skills for data substrate, execution engine, cognitive architecture, and synthesis phases.

Use when asked to profile Python code performance, identify bottlenecks, measure execution time, or analyze function call statistics.