← 返回 Skills 市场
63
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install wheelspotter
功能描述
A wheel-spotting scout that finds reusable solutions before you build from scratch. Cost-controlled intelligent search with complexity-aware filtering, inten...
安全使用建议
This skill appears coherent: it searches public package registries and GitHub and returns recommended integrations. Before installing, check these items: (1) the README/SKILL.md reference requirements.txt but none is bundled — ask the author for the dependency file or inspect search.py to ensure you can satisfy dependencies safely; (2) the skill may perform many outbound API calls (internet access required); if you supply a GitHub token, it will be used for API requests — only provide a token with appropriate, limited scopes; (3) the docs mention caching/vector memory; verify whether the skill writes persistent data (where and with what permissions) if you care about privacy; (4) review the full scripts/search.py (and any omitted/truncated code) for any unexpected external endpoints or persistence logic before enabling the skill in an agent that runs autonomously.
功能分析
Type: OpenClaw Skill
Name: wheelspotter
Version: 1.0.0
WheelSpotter is a legitimate utility designed to help users find existing software libraries and tools across platforms like GitHub, PyPI, npm, Maven, and Crates.io. The core logic in `scripts/search.py` uses standard API requests to fetch project metadata and applies reasonable filters based on project activity and popularity to recommend high-quality results. No evidence of data exfiltration, malicious execution, or prompt injection was found; the script only communicates with official package registries and the instructions in `SKILL.md` are strictly aligned with the tool's stated purpose of reducing redundant development.
能力标签
能力评估
Purpose & Capability
Name/description match the implementation: the script queries GitHub, PyPI, npm, Maven, and crates.io to find reusable libraries/tools. Requested capabilities (complexity-aware filtering, platform selection, cost caps) are consistent with search behavior. Minor inconsistency: the SKILL.md/README instructs 'pip install -r requirements.txt' and references a requirements.txt file, but no requirements.txt appears in the manifest.
Instruction Scope
SKILL.md instructs the agent to perform parallel API calls and return actionable commands (e.g., 'pip install X') — all within the declared purpose. It asks for internet access and optionally a GitHub token (optional, increases rate limits). The docs mention 'result caching', 'vector memory', and 'feedback loops' (progressive improvement) but the manifest doesn't include configuration or storage paths for persistent memory; verify whether persistence is implemented before enabling long-term storage.
Install Mechanism
There is no install spec (instruction-only skill). The included Python script uses the 'requests' library (SKILL.md lists requests and pydantic as dependencies), which is reasonable. The missing requirements.txt referenced in documentation is an implementation gap but not an installation risk by itself.
Credentials
No required environment variables or credentials are declared. SKILL.md/README mention an optional GitHub token to increase API rate limits; that is proportionate to searching GitHub. There are no demands for unrelated secrets or privileged credentials.
Persistence & Privilege
always:false (default) and autonomous invocation is allowed (normal). The skill mentions caching and vector memory but the package manifest does not show storage/config paths or a DB client. Confirm whether the skill will persist search results or feedback and where those artifacts are kept before granting long-term use.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install wheelspotter - 安装完成后，直接呼叫该 Skill 的名称或使用
/wheelspotter触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
WheelSpotter v1.0.0 – Initial release
- Launches an intelligent tool for finding reusable code solutions ("wheels") with complexity-aware search, intent classification, and hard filtering.
- Supports natural language and structured input; offers actionable, integrable recommendations with clear cost and time savings reports.
- Implements adaptive platform selection, multi-stage evaluation, and progressive learning via feedback and caching.
- Provides robust input/output specifications and avoids false positives for non-integrable solutions.
- Triggers on common "wheel-spotting" intents to prevent redundant effort and maximize developer efficiency.
元数据
常见问题
WheelSpotter 是什么？
A wheel-spotting scout that finds reusable solutions before you build from scratch. Cost-controlled intelligent search with complexity-aware filtering, inten... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 63 次。
如何安装 WheelSpotter？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install wheelspotter」即可一键安装，无需额外配置。
WheelSpotter 是免费的吗？
是的，WheelSpotter 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
WheelSpotter 支持哪些平台？
WheelSpotter 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 WheelSpotter？
由 GARYLOooP（@garylooop）开发并维护，当前版本 v1.0.0。
推荐 Skills