Hj Check Test

What This Skill Does

The Hj Check Test skill acts as a comprehensive, FastAPI-based content moderation and quality assurance agent. It is specifically designed to analyze text input for sensitive content, grammatical errors, spelling mistakes, and violations of standardized terminology. By integrating this service, users can ensure that their written content meets organizational, legal, and linguistic standards before publication. The skill functions as a middleware bridge, processing text through a dedicated API to return granular reports on potential issues, including the specific location of errors, the level of severity, and suggested corrections.

Installation

To integrate this skill into your environment, use the OpenClaw command-line interface. Run the following command in your terminal:

clawhub install openclaw/skills/skills/1227323804/hj-check-test

Ensure your system meets the requirements (Python 3.11+). Configure the environment variables, specifically the SAFEGUARD_API_URL, to point to your target detection instance, and verify your connectivity by checking the /health endpoint after starting the service with python main.py.

Use Cases

This skill is highly versatile for content-heavy workflows. Use cases include:

1. Corporate Compliance: Automatically scanning internal memos or public-facing marketing copy for prohibited terminology.
2. Editorial Workflow: Assisting copywriters in identifying typos and non-standard phrasing in real-time.
3. Content Filtering: Cleaning user-generated content in community forums to ensure adherence to safety guidelines.
4. Educational Tools: Providing automated feedback to students on their writing structure and vocabulary accuracy.

Example Prompts

1. "Check this article for any sensitive words or typos: [Insert your draft here]"
2. "Review the following text for compliance with standard terminology guidelines: [Insert your draft here]"
3. "Analyze the following text and explain if there are any critical errors that need immediate correction: [Insert your draft here]"

Tips & Limitations

• Performance: The speed of analysis depends on the configured API_TIMEOUT and the responsiveness of the upstream safety API. For very large documents, consider breaking the text into smaller chunks.
• Context Sensitivity: While the tool is excellent for detecting hard-coded sensitivity patterns, it may not grasp complex, nuanced social subtext. Use it as an assistant rather than a replacement for human editorial judgment.
• Environment: Ensure that the logs/app.log file is monitored periodically to catch connectivity issues with the upstream API, as this is the most common point of failure for this skill.