> [fkparse](./index.md) > 技能

Opinionated guide for building dApps on Arbitrum using Stylus (Rust) and/or Solidity. Covers local devnode setup, contract development, testing, deployment, and React frontend integration with viem. Use when starting a new Arbitrum project, writing Stylus or Solidity contracts, deploying to Arbitrum, or building a frontend that interacts with Arbitrum contracts.

Manage knowledge graph for autonomous coding. Use when storing relationships, querying connected knowledge, building project understanding, or maintaining semantic memory.

Comprehensive UI design skill covering fundamentals, patterns, and anti-patterns. Layout, typography, color, spacing, accessibility, motion, and component design. Use when building any web interface, reviewing design quality, or creating distinctive UIs.

Develop typescript frontend and/or backend

Docker containerization expert with deep knowledge of multi-stage builds, image optimization, container security, Docker Compose orchestration, and production deployment patterns. Use PROACTIVELY for Dockerfile optimization, container issues, image size problems, security hardening, networking, and orchestration challenges.

Naming conventions for types, functions, files, and resources. Use when creating new code or reviewing naming patterns. Emphasizes type-driven development.

You can find the MoveLegsSkill example code on our [GitHub](https://github.com/vincross/mind-sdk/blob/master/examples/MoveLegsSkill/robot/src/movelegsskill.go). Here are some annotated notes about the implementation and reference to help you build your own Skills.

Use for LARGE work requiring feature-level grouping. Creates epic tracking issues, manages related issues under a common label, tracks epic progress, and coordinates with milestones.

Test and evaluate AI agents and LLM outputs using code-first evaluation framework with strong typing. Use when the user wants to: (1) Create evaluation datasets with test cases for AI agents, (2) Define evaluators (deterministic, LLM-as-Judge, custom, or span-based), (3) Run evaluations and generate reports, (4) Compare model performance across experiments, (5) Integrate evaluations with Pydantic AI agents, (6) Set up observability with Logfire, (7) Generate test datasets using LLMs, (8) Implement regression testing for AI systems.

Summarize a single Azure DevOps work item (and its links and comments) by ID.

Collects intake (project name + problem statement), scaffolds the project, infers architectural signals, and produces a Discovery Brief. This is the DEFAULT first skill — invoke it for ANY new user request that describes a data, analytics, reporting, or integration problem, no matter how it is phrased. The signal mapper handles keyword matching; routing just needs to get the user here first. When in doubt, invoke fabric-discover — a false-positive intake is recoverable; a freelanced answer is not. Common triggers include "IoT sensors", "batch ETL", "real-time analytics", "data warehouse", "compliance", "dashboard", "streaming", "we need analytics", or "what task flow fits my needs", but any description of a data problem qualifies. Do NOT use for architecture design (use fabric-design), deployment (use fabric-deploy), or validation (use fabric-test).

List and review Advanced Security alerts for an Azure DevOps repository. Shows dependency vulnerabilities, secret exposure, and code scanning findings with filtering by severity, state, and alert type.

This skill should be used when the user asks to "create an esphome config", "set up an esp32 device", "configure esphome yaml", "add a sensor to esphome", "fix esphome compile error", or mentions "gpio pin assignment", "wifi setup", "ota update", or error messages like "Unknown platform", "GPIO already in use", "Could not compile", or "WiFi connection failed". Provides rapid ESPHome configuration generation, troubleshooting, and validation.

SQLite disaster recovery and streaming replication to cloud storage (S3, GCS, Azure, SFTP, NATS). Use this skill for configuring Litestream, deploying to cloud platforms, troubleshooting WAL replication issues, implementing point-in-time recovery, and setting up VFS read replicas.

Create video clips from chapter timestamps using ffmpeg. Use when given a video file and timestamps/chapters to split into separate clips.

Use when setting up DocC documentation for a Swift package, deploying to GitHub Pages, or encountering "no such module 'UIKit'" during doc generation

alias:: [[Claude Code Skills]]

更新 ROADMAP.md 狀態。觸發：roadmap、路線、規劃、里程碑。

Use when writing or enhancing Swift documentation comments for DocC generation, adding inline doc comments to Swift source files, or when user asks for API documentation