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Found 1,471 Skills
Answer ZenMux questions by reading the latest official docs. Use for product features, APIs, integration, pricing, models/providers, routing, fallback, streaming, multimodal, structured output, tool calling, reasoning, prompt caching, image/video generation, web search, long context, observability, logs, cost tracking, subscriptions, PAYG, invoices, FAQ, privacy, terms, compliance, and tool guides for Claude Code, Cursor, Cline, Codex, Gemini CLI, opencode, Cherry Studio, Obsidian, Sider, Open-WebUI, Dify, and GitHub Copilot. Trigger on "ZenMux docs", "ZenMux API", "how to use ZenMux", "models", "pricing", "ZenMux 怎么用", "文档", "快速开始", "API 参考", "模型路由", "供应商路由", "订阅", "按量计费", "接入", "配置". Also use when ZenMux is the project context and the user asks about LLM API aggregation, model routing, or provider fallback.
Performs an architectural and quality code review on a specified file or set of files. Checks for coding standard compliance, architectural pattern adherence, SOLID principles, testability, and performance concerns.
Generate and modify Vue 3, TypeScript, and SCSS code in compliance with project standards.
Validates Claude Code plugins against architectural best practices for Agents, Skills, MCP, and Progressive Disclosure. Use when validating plugin structure, reviewing manifest files, checking frontmatter compliance, or verifying tool invocation patterns.
Analyze debt covenants and credit agreement terms from SEC filings using Octagon MCP. Use when researching financial covenants, leverage ratios, interest coverage requirements, credit facilities, debt maturity schedules, and covenant compliance from 10-K, 10-Q, and 8-K filings.
Test, validate, and improve agent instructions (CLAUDE.md, system prompts) using sub-agents as experiment subjects. Measures instruction compliance, context decay, and constraint strength. Use for "test prompt", "validate instructions", "prompt effectiveness", "instruction decay", or when designing robust agent behaviors.
Code review skill for quality, standards compliance, and best practices
Know when your AI breaks in production. Use when you need to monitor AI quality, track accuracy over time, detect model degradation, set up alerts for AI failures, log predictions, measure production quality, catch when a model provider changes behavior, build an AI monitoring dashboard, or prove your AI is still working for compliance. Covers DSPy evaluation for ongoing monitoring, prediction logging, drift detection, and alerting.
Professional WordPress plugin development best practices following our project structure with composer, namespaced classes, wp-env testing, WPCS compliance, and proper plugin architecture. Use this when working on WordPress plugin code.
Builds dashboards, reports, and data-driven interfaces requiring charts, graphs, or visual analytics. Provides systematic framework for selecting appropriate visualizations based on data characteristics and analytical purpose. Includes 24+ visualization types organized by purpose (trends, comparisons, distributions, relationships, flows, hierarchies, geospatial), accessibility patterns (WCAG 2.1 AA compliance), colorblind-safe palettes, and performance optimization strategies. Use when creating visualizations, choosing chart types, displaying data graphically, or designing data interfaces.
Generate analytics reports from Olakai data using CLI commands. AUTO-INVOKE when user wants: usage summaries, KPI trends, risk analysis, ROI reports, efficiency metrics, agent comparisons, token usage reports, cost analysis, compliance reports, or any analytics without using the web dashboard. TRIGGER KEYWORDS: olakai, analytics, reports, usage summary, KPI trends, risk analysis, ROI, efficiency, agent comparison, token usage, cost analysis, metrics report, dashboard data, CLI analytics, terminal report, compliance, usage report, event summary, performance metrics, AI usage stats. DO NOT load for: setting up monitoring (use olakai-add-monitoring), troubleshooting (use olakai-troubleshoot), or creating new agents (use olakai-create-agent).
Analyze HM Desktop PRD documents, extract requirement information, verify completeness, check chapter order (Requirement Source → Requirement Background → Requirement Value Analysis → Competitor Analysis → Requirement Description), inspect KEP definitions, detect requirement conflicts, and generate structured analysis reports. Applicable to user requests: (1) Analyze or review PRD documents, (2) Extract KEP lists from requirements, (3) Check PRD completeness or consistency, (4) Map requirements to module architecture, (5) Verify PRD format compliance, (6) Verify completeness of competitor analysis chapters. Keywords: PRD analysis, requirement extraction, KEP verification, completeness check, chapter order validation, competitor analysis check, analyze PRD, requirement extraction, completeness check, chapter order validation