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aronchick

Expanso text-summarize

by Expanso · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
865
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0
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1
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1
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Install in OpenClaw
/install expanso-text-summarize
Description
Summarize input text into 3-5 concise bullet points using AI with Expanso Edge.
README (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
Usage Guidance
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:${PORT}. Only run it on a machine/network you control, and bind to localhost if you don't want external access. - The README suggests a 'deploy to Expanso Cloud' step — deploying will send the pipeline YAML to that service; confirm you understand what will be uploaded and that you are comfortable doing so. - Install expanso-edge from a trusted source (the README suggests clawhub) and inspect the binary/tools you install. - If privacy is critical, prefer the Ollama/local backend option so no external LLM calls occur. If you proceed, test locally with non-sensitive text and monitor logs to confirm keys are not transmitted.
Capability Analysis
Type: OpenClaw Skill Name: expanso-text-summarize Version: 1.0.0 The skill bundle provides a text summarization tool using AI, designed to keep API keys local to the user's machine. All files, including `SKILL.md` and `README.md`, describe the skill's functionality and usage without any evidence of malicious intent, data exfiltration, unauthorized execution, or prompt injection attempts against the OpenClaw agent. The `pipeline-cli.yaml` and `pipeline-mcp.yaml` files use standard Expanso Edge processors to interact with OpenAI, explicitly resolving `OPENAI_API_KEY` locally, aligning with the stated security posture.
Capability Assessment
Purpose & Capability
The skill's stated purpose (text summarization) matches the pipelines and files. However, the registry metadata claims no required environment variables while the pipelines and README clearly reference an OPENAI_API_KEY (unless using Ollama). That mismatch between declared requirements and actual runtime needs is an incoherence that should be resolved before trusting the skill.
Instruction Scope
The SKILL.md and pipeline YAMLs stay within the summarization scope: they read input, compute hashes for audit, call an LLM backend, format output, and log. Things to note: (1) MCP mode starts an HTTP server bound to 0.0.0.0:${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.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install expanso-text-summarize
  3. After installation, invoke the skill by name or use /expanso-text-summarize
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial publish to ClawHub
Metadata
Slug expanso-text-summarize
Version 1.0.0
License
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Expanso text-summarize?

Summarize input text into 3-5 concise bullet points using AI with Expanso Edge. It is an AI Agent Skill for Claude Code / OpenClaw, with 865 downloads so far.

How do I install Expanso text-summarize?

Run "/install expanso-text-summarize" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Expanso text-summarize free?

Yes, Expanso text-summarize is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Expanso text-summarize support?

Expanso text-summarize is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Expanso text-summarize?

It is built and maintained by Expanso (@aronchick); the current version is v1.0.0.

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