← 返回 Skills 市场
aronchick

Expanso text-summarize

作者 Expanso · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
865
总下载
0
收藏
1
当前安装
1
版本数
在 OpenClaw 中安装
/install expanso-text-summarize
功能描述
Summarize input text into 3-5 concise bullet points using AI with Expanso Edge.
使用说明 (SKILL.md)

text-summarize

Summarize text into 3-5 bullet points using AI

Requirements

  • Expanso Edge installed (expanso-edge binary in PATH)
  • Install via: clawhub install expanso-edge

Usage

CLI Pipeline

# Run standalone
echo '\x3Cinput>' | expanso-edge run pipeline-cli.yaml

MCP Pipeline

# Start as MCP server
expanso-edge run pipeline-mcp.yaml

Deploy to Expanso Cloud

expanso-cli job deploy https://skills.expanso.io/text-summarize/pipeline-cli.yaml

Files

File Purpose
skill.yaml Skill metadata (inputs, outputs, credentials)
pipeline-cli.yaml Standalone CLI pipeline
pipeline-mcp.yaml MCP server pipeline
安全使用建议
What to check before installing: - Confirm the OPENAI_API_KEY requirement: the pipelines and README use OPENAI_API_KEY. If you don't want to use OpenAI, switch the pipeline to a local Ollama backend as documented. - Verify registry metadata accuracy: the skill should declare OPENAI_API_KEY if it's needed. Mismatched metadata is a warning sign. - Be aware MCP mode starts an HTTP server on 0.0.0.0:${PORT}. Only run it on a machine/network you control, and bind to localhost if you don't want external access. - The README suggests a 'deploy to Expanso Cloud' step — deploying will send the pipeline YAML to that service; confirm you understand what will be uploaded and that you are comfortable doing so. - Install expanso-edge from a trusted source (the README suggests clawhub) and inspect the binary/tools you install. - If privacy is critical, prefer the Ollama/local backend option so no external LLM calls occur. If you proceed, test locally with non-sensitive text and monitor logs to confirm keys are not transmitted.
功能分析
Type: OpenClaw Skill Name: expanso-text-summarize Version: 1.0.0 The skill bundle provides a text summarization tool using AI, designed to keep API keys local to the user's machine. All files, including `SKILL.md` and `README.md`, describe the skill's functionality and usage without any evidence of malicious intent, data exfiltration, unauthorized execution, or prompt injection attempts against the OpenClaw agent. The `pipeline-cli.yaml` and `pipeline-mcp.yaml` files use standard Expanso Edge processors to interact with OpenAI, explicitly resolving `OPENAI_API_KEY` locally, aligning with the stated security posture.
能力评估
Purpose & Capability
The skill's stated purpose (text summarization) matches the pipelines and files. However, the registry metadata claims no required environment variables while the pipelines and README clearly reference an OPENAI_API_KEY (unless using Ollama). That mismatch between declared requirements and actual runtime needs is an incoherence that should be resolved before trusting the skill.
Instruction Scope
The SKILL.md and pipeline YAMLs stay within the summarization scope: they read input, compute hashes for audit, call an LLM backend, format output, and log. Things to note: (1) MCP mode starts an HTTP server bound to 0.0.0.0:${PORT}, which exposes an endpoint that will accept text to summarize — ensure you understand network exposure; (2) README and SKILL.md offer a 'deploy to Expanso Cloud' command that would send the pipeline to an external service (the pipeline YAML itself, not your API key), so be cautious about what you deploy.
Install Mechanism
This is instruction-only (no install spec or code files to execute). It requires the expanso-edge binary to be present; the README suggests installing via `clawhub install expanso-edge`. No archives or remote downloads are embedded in the skill package itself.
Credentials
The runtime expects OPENAI_API_KEY (and optionally PORT), and skill.yaml lists OPENAI_API_KEY as a credential (marked not required if using Ollama). But the registry metadata lists no required env vars — an inconsistency. Requesting an API key for the LLM backend is reasonable for this skill, but it should be declared consistently in the registry metadata and install/instructions. Also note: if you run in MCP mode, callers can send arbitrary text; the key remains local, but traffic to the model will consume your quota.
Persistence & Privilege
The skill does not request permanent presence (always:false) and does not modify other skills or system configs. Running an MCP server binds a port (potential network exposure), but that is within the expected behavior for an HTTP-backed pipeline.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install expanso-text-summarize
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /expanso-text-summarize 触发
  4. 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
Initial publish to ClawHub
元数据
Slug expanso-text-summarize
版本 1.0.0
许可证
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Expanso text-summarize 是什么?

Summarize input text into 3-5 concise bullet points using AI with Expanso Edge. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 865 次。

如何安装 Expanso text-summarize?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install expanso-text-summarize」即可一键安装,无需额外配置。

Expanso text-summarize 是免费的吗?

是的,Expanso text-summarize 完全免费(开源免费),可自由下载、安装和使用。

Expanso text-summarize 支持哪些平台?

Expanso text-summarize 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 Expanso text-summarize?

由 Expanso(@aronchick)开发并维护,当前版本 v1.0.0。

💬 留言讨论