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Install in OpenClaw
/install brunch-spots
Description
Find nearby brunch spots. Invoke when user asks for brunch near me.
README (SKILL.md)
Nearby Brunch Spots
用途
- 提供用户当前位置附近的 Brunch Spots 列表
- 统一返回字段与查询行为，便于前端/接口复用
- 适用于“早午餐/周末 brunch/排队热门店”查询场景
触发条件
- 用户询问“Brunch Spots 附近 / brunch near me / nearby brunch”
- 用户提供定位/城市并希望“找/推荐/看看附近的 Brunch Spots”
输入参数
- location: 经纬度 { lat, lng }，必填
- radius_meters: 查询半径，默认 3000
- limit: 返回数量上限，默认 20，最大 50
- filters: 可选筛选（open_now、min_rating、price_level、keywords 等）
响应字段
- 统一参见 STANDARD_RESPONSE.md
- 本技能 category 固定为 "brunch-spots"
错误码
- INVALID_LOCATION: 经纬度不合法
- RADIUS_TOO_LARGE: 超过最大查询半径
- PROVIDER_UNAVAILABLE: 数据源不可用
- RATE_LIMITED: 触发速率限制
示例
- 输入: { location: { lat: 30.123, lng: 120.456 }, radius_meters: 2500, limit: 10, filters: { min_rating: 4.3 } }
- 输出: 标准 POI 列表（见 STANDARD_RESPONSE.md）
隐私与速率限制
- 仅在用户授权定位后查询
- 避免保留精确坐标，必要时进行网格化模糊处理
- 建议对同一 location+category+radius 做短时缓存以降低频率
Usage Guidance
This skill appears to do what it says (list nearby brunch spots) but leaves important runtime details unspecified. Before installing, ask the publisher or platform: (1) Where should the skill obtain POI data? Which provider(s) are allowed? (2) Is STANDARD_RESPONSE.md available in your environment or part of the platform schema? (3) If external APIs are used, what credentials will be required and how will they be stored? (4) Confirm the agent will not send precise coordinates to arbitrary third parties — ask for an allowlist of endpoints or an explicit data-flow description. If you cannot get those answers, treat the skill as risky because it could prompt you for API keys or call external services unexpectedly.
Capability Analysis
Type: OpenClaw Skill
Name: brunch-spots
Version: 0.1.0
The skill bundle consists of metadata and documentation (SKILL.md) for a 'Nearby Brunch Spots' feature. It defines standard input parameters (location, radius) and response formats without any executable code, suspicious network calls, or prompt-injection risks. The instructions focus on legitimate functionality and include privacy-conscious guidelines such as requiring user authorization for location data.
Capability Assessment
Purpose & Capability
Name/description align with returning nearby brunch POIs. However, the skill does not declare where POI data should come from (no provider, API, or required credentials listed) and references STANDARD_RESPONSE.md which is not included — this gap makes it unclear what external access or secrets would actually be needed.
Instruction Scope
SKILL.md stays on-topic (expects lat/lng input, radius, filters, and defines response and error codes). It also contains privacy guidance (request consent, blur coords). But instructions are vague about how to obtain data: they don't specify allowed endpoints, APIs, or prohibited actions, so an agent could fallback to web-scraping, calling third-party APIs, or requesting API keys at runtime.
Install Mechanism
Instruction-only skill with no install spec and no code files — lowest installation risk. Nothing will be written to disk by an installer.
Credentials
The skill declares no environment variables or credentials, which is coherent if the platform supplies a POI provider. However, fetching POI data commonly requires e.g., Google/Mapbox/Here API keys; the absence of any declared credentials is a potential mismatch unless the runtime platform provides the service implicitly.
Persistence & Privilege
always is false and the skill does not request persistent system-wide changes. No indications it modifies other skills or agent configs.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install brunch-spots - After installation, invoke the skill by name or use
/brunch-spots - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Nearby Brunch Spots skill initial release:
- Find brunch spots near your current location with customizable filters (radius, rating, price, etc.).
- Returns a standardized list of locations for consistent frontend and API integration.
- Requires user location and supports privacy by avoiding storage of exact coordinates.
- Includes error handling for invalid location, excessive radius, data source issues, and rate limiting.
- Supports caching to optimize repeat queries for the same search area.
Metadata
Frequently Asked Questions
What is Nearby Brunch Spots?
Find nearby brunch spots. Invoke when user asks for brunch near me. It is an AI Agent Skill for Claude Code / OpenClaw, with 112 downloads so far.
How do I install Nearby Brunch Spots?
Run "/install brunch-spots" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Nearby Brunch Spots free?
Yes, Nearby Brunch Spots is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Nearby Brunch Spots support?
Nearby Brunch Spots is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Nearby Brunch Spots?
It is built and maintained by clawkk (@clawkk); the current version is v0.1.0.
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