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Install in OpenClaw
/install bars
Description
Find nearby bars. Invoke when user asks for drinks or nightlife near me.
README (SKILL.md)
Nearby Bars
用途
- 提供用户当前位置附近的 Bars 列表
- 统一返回字段与查询行为，便于前端/接口复用
- 支持常见筛选（评分、价格等级、是否营业、关键词等）
触发条件
- 用户询问“Bars 附近 / bars near me / nearby bars / nightlife”
- 用户提供定位/城市并希望“找/推荐/看看附近的 Bars”
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 "bars"
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: 3000, limit: 10, filters: { open_now: true } }
- 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 coherent and low-risk: it expects a user-provided location and returns nearby bars. Before installing, confirm how the agent will obtain POI data (the SKILL.md does not specify a provider or API) and where network calls will be sent. Ensure the agent obtains explicit user consent for location sharing, follow the doc's recommendation to avoid storing precise coordinates (use blurring/gridizing if required), and define the STANDARD_RESPONSE schema you will use. Because this is instruction-only (no code to inspect), verify at integration time what concrete implementation (APIs, keys, rate limits, logging) the agent will use to execute the queries.
Capability Assessment
Purpose & Capability
Name and description ('Nearby Bars') match the instructions: the skill expects a location and returns nearby bar POIs with filtering options. It does not request unrelated credentials, binaries, or config paths.
Instruction Scope
Instructions stay within the stated purpose (query POIs for provided lat/lng, support filters, rate limiting, and privacy recommendations). However the doc references STANDARD_RESPONSE.md (response schema) which is not included in the package; the absence of a specified data provider/API (how POIs are sourced) is a missing implementation detail that an integrator must supply.
Install Mechanism
No install spec and no code files are present (instruction-only). This minimizes on-disk install risk.
Credentials
No environment variables, credentials, or config paths are requested — proportional to the skill's purpose.
Persistence & Privilege
Skill does not request always:true and makes no claims about modifying other skills or system config. Normal autonomous invocation settings apply.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install bars - After installation, invoke the skill by name or use
/bars - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Nearby Bars v0.1.0
- Initial release with core functionality for finding nearby bars.
- Supports location-based search with filters (open now, min rating, price level, keywords).
- Returns consistent POI responses according to a standard schema.
- Handles typical user queries for bars or nightlife in the area.
- Implements error codes for invalid input, provider issues, and rate limiting.
- Includes privacy safeguards and short-term caching recommendations.
Metadata
Frequently Asked Questions
What is Nearby Bars?
Find nearby bars. Invoke when user asks for drinks or nightlife near me. It is an AI Agent Skill for Claude Code / OpenClaw, with 139 downloads so far.
How do I install Nearby Bars?
Run "/install bars" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Nearby Bars free?
Yes, Nearby Bars is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Nearby Bars support?
Nearby Bars is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Nearby Bars?
It is built and maintained by ClawKK (@codekungfu); the current version is v0.1.0.
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