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Install in OpenClaw
/install product-test-skill
Description
Processes CSV files to generate statistical summaries (mean, median, std, min, max) for specified numeric columns and row count.
Usage Guidance
This skill appears coherent and low-risk: it only needs to read a local CSV and compute statistics. Before installing, ensure you are comfortable with the agent having access to the local files you provide (do not point it at sensitive data). Also ensure the execution environment has the required Python packages (pandas >=2.0.0, numpy >=1.24.0) or that you trust the environment to install them. Finally, verify the platform's runtime network/file permissions since the skill's SKILL.md claims no network access — platforms can still grant broader permissions at runtime.
Capability Analysis
Type: OpenClaw Skill
Name: product-test-skill
Version: 1.0.0
The skill bundle contains metadata and documentation for a standard CSV data analysis tool. The instructions in skill.md describe basic statistical processing using pandas and numpy with local file access and no network requirements, showing no signs of malicious intent or prompt injection.
Capability Assessment
Purpose & Capability
Name/description (CSV statistical summaries) align with the inputs, outputs, and declared dependencies (pandas, numpy). There is no request for unrelated credentials, binaries, or config paths.
Instruction Scope
SKILL.md explicitly limits actions to reading a provided local CSV path and computing statistics; it states no network access is required. The instructions do not ask the agent to read unrelated files, environment variables, or transmit data to external endpoints.
Install Mechanism
This is an instruction-only skill (no install spec, no code). That is low risk. It lists pandas and numpy as dependencies but provides no install mechanism — not a security problem but means the runtime must already have (or be allowed to install) those packages.
Credentials
The skill requests no environment variables, credentials, or config paths. The scope of access (local file read) is proportionate to the stated purpose.
Persistence & Privilege
The skill does not request always: true, does not modify other skills, and does not claim persistent/system-wide changes. Autonomous invocation is allowed (platform default) but not combined with other red flags.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install product-test-skill - After installation, invoke the skill by name or use
/product-test-skill - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of the self-improvement logging skill for OpenClaw and generic agents.
- Captures learnings, user corrections, errors, and feature requests in standardized markdown files under `.learnings/`.
- Includes initialization instructions to set up `.learnings/LEARNINGS.md`, `ERRORS.md`, and `FEATURE_REQUESTS.md` with clear file formats.
- Provides detailed workflows for logging, promoting broadly applicable insights to workspace knowledge files, and maintaining safe handling of sensitive information.
- Integrates with OpenClaw for automated reminders and cross-session learning sharing; also outlines generic usage for other agents.
Metadata
Frequently Asked Questions
What is test-skill?
Processes CSV files to generate statistical summaries (mean, median, std, min, max) for specified numeric columns and row count. It is an AI Agent Skill for Claude Code / OpenClaw, with 49 downloads so far.
How do I install test-skill?
Run "/install product-test-skill" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is test-skill free?
Yes, test-skill is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does test-skill support?
test-skill is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created test-skill?
It is built and maintained by aidfsoft (@aidfsoft); the current version is v1.0.0.
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