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Install in OpenClaw
/install coworking-spaces
Description
Find nearby coworking spaces. Invoke when user asks for shared offices near me.
README (SKILL.md)
Nearby Coworking Spaces
用途
- 提供用户当前位置附近的 Coworking Spaces 共享办公列表
- 统一返回字段与查询行为，便于前端/接口复用
触发条件
- 用户询问“共享办公 附近 / coworking spaces near me / shared offices”
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（是否按日租、会议室、咖啡、评分等）
响应字段
- 统一参见 STANDARD_RESPONSE.md
- 本技能 category 固定为 "coworking-spaces"
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 }
- 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
Usage Guidance
This skill's goal (find coworking spaces nearby) is reasonable, but the runtime instructions are incomplete. Before installing or using it, ask the author: (1) What data source(s) does the skill use to get POIs? Will it call Google Maps, Foursquare, OpenStreetMap, or another API? (2) If it uses an external API, what credentials will be required and how will they be stored? (3) Why does the SKILL.md reference a local file path (STANDARD_RESPONSE.md) that likely doesn't exist in your environment? Practical risks: the agent may attempt arbitrary web queries or call third-party APIs without explicit credential declarations, and the local file reference could cause failures or unexpected behavior. If you need to proceed, require the skill author to document the provider(s), any required API keys, and replace local file references with an included schema or a stable URL.
Capability Analysis
Type: OpenClaw Skill
Name: coworking-spaces
Version: 0.1.0
The skill bundle consists of documentation (SKILL.md) defining parameters and logic for finding nearby coworking spaces. It contains no executable code, network requests, or instructions that would lead to data exfiltration or unauthorized system access. A local file path reference in SKILL.md appears to be a development artifact rather than a malicious indicator.
Capability Assessment
Purpose & Capability
The skill claims to return nearby coworking POIs, but provides no mechanism for obtaining that data (no API endpoints, no web-scrape instructions, no built-in dataset). A skill that performs POI lookup would normally declare required API keys or an explicit provider; the absence of any data-source or credential requirement is incoherent with the stated capability.
Instruction Scope
SKILL.md defines inputs/outputs and privacy guidance, which is appropriate, but it references an absolute local file URI (file:///Users/mac_lkm/.../STANDARD_RESPONSE.md). That implies the skill expects access to a developer's local filesystem or another repo file that won't exist for most users. The instructions also do not state what external endpoints (maps, directories) to query or how to fetch POIs, leaving the agent broad discretion to choose data sources.
Install Mechanism
Instruction-only skill with no install spec and no code files — lowest install risk. Nothing written to disk or downloaded by the skill itself.
Credentials
The skill declares no environment variables or credentials. However, returning live POIs normally requires API keys (e.g., Google Maps, Foursquare, OpenStreetMap providers) or at least a documented data source. The lack of declared credentials is unexpected and could mean the agent will attempt to use general web access or built-in browsing instead—this should be clarified.
Persistence & Privilege
always:false and no special system/config modifications requested. The skill does not request persistent presence or elevated privileges.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install coworking-spaces - After installation, invoke the skill by name or use
/coworking-spaces - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Initial release of the "附近共享办公" skill:
- Provides lists of nearby coworking spaces based on user location.
- Supports query customization with radius, result limits, and optional filters (daily rental, meeting rooms, coffee, rating, etc.).
- Returns standardized results to ensure easy reuse across platforms.
- Includes error handling for invalid input, too-large search areas, data source issues, and rate limits.
- Location queries require user consent and may apply privacy-preserving techniques.
Metadata
Frequently Asked Questions
What is Coworking Spaces?
Find nearby coworking spaces. Invoke when user asks for shared offices near me. It is an AI Agent Skill for Claude Code / OpenClaw, with 107 downloads so far.
How do I install Coworking Spaces?
Run "/install coworking-spaces" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Coworking Spaces free?
Yes, Coworking Spaces is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Coworking Spaces support?
Coworking Spaces is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Coworking Spaces?
It is built and maintained by ClawKK (@codekungfu); the current version is v0.1.0.
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