Use when the user wants to develop, run, preview, save, deploy, or roll back a CloudBase Web app in this conversation as a Lovable/Codex-Sites-like vibe- coding session — i.e. any request that maps to "spin up a React+Vite project, see it live in the browser, iterate, save versions, deploy". Activate ONLY for browser-rendered Web projects based on the CloudBase official React (or Vue) + Vite template. Do NOT activate for: WeChat/Alipay mini-program, React Native / Flutter / Electron, pure cloud functions / CloudRun backends, or Next.js / Nuxt / Astro / Remix / SvelteKit (those frameworks are explicitly out of scope).

CloudBase Run backend development rules (Function mode/Container mode). Use this skill when deploying backend services that require long connections, multi-language support, custom environments, AI agent development, or migrating existing/GitHub apps that need VPC access to MySQL/PostgreSQL/Redis. Also use when diagnosing CloudRun container deploy failures (deploy_failed, readiness/probe failed, image won't start, docker.io pull loops). For stateless HTTP services, prefer HTTP cloud functions.

Validates equivalence between LiteRT models (litert_lm) and PyTorch models (transformers). Use when you need to verify that an exported LiteRT model produces the same outputs as the original Hugging Face model. Supports multi-turn conversations and custom prompts.

Use when the user wants to run XCUITests, parse test results, view test failures, or export test attachments.

Use this agent to scan Swift code for camera, video, and audio capture issues including deprecated APIs, missing interruption handlers, threading violations, and permission anti-patterns.

Use when building a managed team skills library for a real stack. Map work to shelves, browse before curating, write meaningful `whyHere` notes, and create a starter pack once the first pass is solid.

Examines a specific product's detailed page to verify it matches the user's requirements, checking price, description, features, and reviews. Use when you have navigated to a product detail page from search results and need to confirm the product meets all user-specified constraints before purchasing. It provides a final suitability assessment with a clear proceed-or-reject recommendation.

Analyzes user instructions in ScienceWorld environments to extract specific task requirements and constraints. Use when receiving a new task to identify required objects, target locations, and action sequences before taking any environment actions.

Teleports the agent to a specified room within the ScienceWorld environment. Use when the agent needs to move between different locations to locate objects or access specific facilities. The input is a target room name, and the output is the agent arriving at that room, ready for further interaction.

This skill chemically mixes the contents of a container using the 'mix' action. Use when all required ingredients (e.g., sodium chloride and water) are present inside a container and the agent needs to combine them to produce a new substance. The skill performs the mixing operation and outputs the resulting product, completing the synthesis step of the task.

Use when you have planted a seed or need to track a plant's growth stage (sprouting, flowering, reproduction). Applies the 'focus on' action to a specific plant or biological entity to signal intent and monitor its development. Trigger after planting or when you need to observe life cycle progression in the ScienceWorld environment.

Places an object into one of several designated containers based on a measured condition, such as a temperature threshold. Use this skill when you have completed a measurement or assessment and the task requires sorting or storing the object into one of multiple containers according to a rule (e.g., "if temperature > X, place in container A; otherwise container B").

Use when the agent needs to check whether an ALFWorld task objective has been met after completing a sub-action (e.g., placing an object). This skill parses the task goal, evaluates the latest environment observation, and outputs a verification decision — task complete, task incomplete, or action ineffective — to guide the next step.

Use when the agent is holding an object and needs to place it into a target receptacle in ALFWorld. This skill checks receptacle suitability, opens closed containers if needed, and executes the `put` command to store the object. It handles both open surfaces (countertops, beds) and closed containers (drawers, cabinets).

Prepares a household appliance (microwave, oven, toaster, fridge) for use by ensuring it is in the correct open/closed state. Use when the agent needs to heat, cool, or cook an item and must first open or close the appliance before placing an object inside. Takes an appliance identifier as input and outputs a confirmation that the appliance is ready for the next action.

Use when creating a single Agentlas agent, creating a multi-agent team, or packaging an existing local/external agent into Agentlas architecture. Make sure to use this for /meta-agent requests.

**WORKFLOW SKILL** - Evaluate AI agent skills using structured benchmarks with YAML specs, fixture isolation, and pluggable validators. USE FOR: run waza, waza help, run eval, run benchmark, evaluate skill, test agent, generate eval suite, init eval, compare results, score agent, agent evaluation, skill testing, cross-model comparison. DO NOT USE FOR: improving skill frontmatter (use waza dev), creating new skills from scratch (use skill-creator), token counting or budget checks (use waza tokens). INVOKES: Copilot SDK executor, mock engine, code/regex validators. FOR SINGLE OPERATIONS: use waza run directly for a single benchmark.

Install skills from a zip URL or local zip file path. Use this skill whenever the user wants to install a skill from a zip link or a local file, or uses commands like /skill-add with a URL or file path. Trigger on phrases like: install skill, install from zip, skill from zip, skill from url, add skill from zip, 安装skill, 从zip安装skill, 从本地安装skill.

Detect, configure, and use a conda-compatible tool. Use before tasks that need the project environment, such as importing project code, running tests, building docs, or invoking repo tooling.

Interact with the Stakr protocol — ERC-4626 vaults with multi-reward staking. Use when the user or an agent needs to work with Stakr vaults, add or modify rewards (addRewardToken, addRewards, modifyRewardToken, modifyReward), create or manage an "agent vault" or "own vault", fund incentive programs, configure reward schedules, or integrate Stakr in scripts or tooling. Prefer this skill whenever Stakr, StakrVault, rewards, staking, or vault ownership is mentioned.