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在 OpenClaw 中安装
/install sentiment-score
功能描述
Analyze text sentiment on a scale from -1 (negative) to +1 (positive) using Expanso Edge pipelines.
安全使用建议
This skill appears to do what it claims (sentiment scoring via Expanso pipelines) but there are important mismatches you should address before using it: (1) The SKILL.md and pipeline YAML require the expanso-edge binary and an OPENAI_API_KEY, but the registry metadata omitted those requirements — confirm you can and should install expanso-edge and supply an OpenAI key. (2) The service will send any input text to OpenAI; do not pass secrets, PII, or sensitive documents unless you accept that external transmission and any associated billing. (3) The MCP mode listens on 0.0.0.0 by default — only run that behind appropriate network controls. (4) The SKILL.md suggests deploying to skills.expanso.io — deploying to a third-party cloud will transfer the pipeline; review the pipeline files and trust boundaries before uploading. If you want to proceed, verify the expanso-edge/clawhub sources, explicitly set and scope OPENAI_API_KEY, and test locally with non-sensitive inputs first.
功能分析
Type: OpenClaw Skill
Name: sentiment-score
Version: 1.0.1
The skill is designed for sentiment analysis using an LLM, as described in `SKILL.md` and `README.md`. It uses `OPENAI_API_KEY` from environment variables for authentication with OpenAI, which is a standard security practice. The `pipeline-cli.yaml` and `pipeline-mcp.yaml` files construct prompts to send user input to the LLM and parse its JSON response. There is no evidence of intentional harmful behavior such as data exfiltration, unauthorized command execution, persistence mechanisms, or prompt injection attempts against the OpenClaw agent itself. While passing user input directly to an LLM can introduce prompt injection vulnerabilities against the LLM, this is an inherent risk of LLM applications and not indicative of malicious intent by the skill developer in this context.
能力评估
Purpose & Capability
The pipelines and SKILL.md clearly implement sentiment scoring using Expanso Edge pipelines and an OpenAI chat completion. That capability matches the name and description. However, the registry-level metadata provided to you earlier claims no required binaries or env vars, while the SKILL.md and pipeline YAMLs require the expanso-edge binary and reference OPENAI_API_KEY. This is an inconsistency in declared requirements (likely an omission) that you should verify.
Instruction Scope
The runtime instructions are narrowly scoped to: run a local CLI pipeline, optionally start an HTTP MCP server (/score), or deploy the pipeline to Expanso Cloud. The pipelines only gather the input text and call openai_chat_completion; they do not reference unrelated system files or other environment variables. The MCP pipeline binds to 0.0.0.0:${PORT:-8080} (exposes a network endpoint) which is expected for a server mode but is a surface you should consider when deploying.
Install Mechanism
This is an instruction-only skill with no install spec or bundled code, so nothing is written by the registry itself. The SKILL.md instructs users to install 'expanso-edge' (via 'clawhub install expanso-edge') and to use 'expanso-cli' to deploy. Those external install steps are reasonable for an Expanso pipeline but are not reflected in the registry's declared install requirements — verify provenance of 'clawhub' packages and the expanso-edge binary before installing.
Credentials
The pipelines call openai_chat_completion with api_key: "${OPENAI_API_KEY}" and will transmit input text to OpenAI. Yet the skill metadata provided earlier listed no required env vars; skill.yaml lists OPENAI_API_KEY but marks it required: false. This is disproportionate/ambiguous: the pipeline will either fail without a key or use whatever OPENAI_API_KEY is present in the environment. If you run this, user-provided text (possibly sensitive) will be sent to OpenAI — ensure you are comfortable with that and that the key used has appropriate scope and billing controls.
Persistence & Privilege
The skill does not request permanent presence (always: false) and does not modify other skills or global agent settings. Running the MCP pipeline will open a network listener (user-controlled) but there is no evidence the skill attempts to persist credentials or alter system-wide configuration.
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 sentiment-score - 安装完成后,直接呼叫该 Skill 的名称或使用
/sentiment-score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
v1.0.1
- Updated skill.yaml metadata for clarity and accuracy.
- No changes to functionality or usage instructions.
v1.0.0
Initial release of sentiment-score
- Adds sentiment scoring for text from -1 (negative) to +1 (positive).
- Provides CLI and MCP server usage examples.
- Includes guides for deployment to Expanso Cloud.
- Lists required files and installation steps.
元数据
常见问题
Sentiment Score 是什么?
Analyze text sentiment on a scale from -1 (negative) to +1 (positive) using Expanso Edge pipelines. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 743 次。
如何安装 Sentiment Score?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install sentiment-score」即可一键安装,无需额外配置。
Sentiment Score 是免费的吗?
是的,Sentiment Score 完全免费(开源免费),可自由下载、安装和使用。
Sentiment Score 支持哪些平台?
Sentiment Score 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 Sentiment Score?
由 Expanso(@aronchick)开发并维护,当前版本 v1.0.1。
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