Response Tone Polisher

Polishes response letters by transforming defensive or harsh language into professional, courteous academic prose. Converts phrases like "I will not correct...

This skill appears coherent and focused: it processes reviewer comments and draft responses locally using regex templates and returns polished text. Before installing or running it, consider: 1) Privacy—responses/reviewer comments can be confidential, so run the script in a trusted/local environment and confirm your agent runtime won't forward text to external services. 2) Review the full main.py if you plan to run it in sensitive contexts (the code is bundled but you should confirm there are no unexpected network calls in the truncated portions). 3) Check Python version: the requirements file lists dataclasses/enum (dataclasses is built-in on Python 3.7+), so ensure compatibility. 4) Expect occasional minor formatting/placeholder issues (some replacement strings include placeholders like {noun}/{verb}); evaluate outputs before sending them to editors. If those points are acceptable, the package is proportionate to its stated purpose.

Type: OpenClaw Skill Name: response-tone-polisher Version: 0.1.0 The skill is a text-processing utility designed to polish academic response letters, but it contains a significant vulnerability in its file-handling logic. In `scripts/main.py`, the script implicitly checks if the input strings (`reviewer_comment` and `draft_response`) are valid file paths using `os.path.isfile()` and, if so, reads the file contents without any path sanitization or directory traversal checks. This behavior, combined with the unchecked security items in the `SKILL.md` checklist (e.g., 'Input file paths validated'), creates a risk where an attacker could trick the agent into reading sensitive local files by providing their paths as input text.