Error Prone
v1.0.0Makes AI-generated text sound more human by intentionally introducing realistic imperfections. Use when writing emails, messages, social posts, or any text t...
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byDylan Feltus@dylanfeltus
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description match the SKILL.md. The skill is instruction-only and only describes text transformations (typos, contractions, tone). It does not request unrelated binaries, environment variables, or config paths.
Instruction Scope
Instructions stay within text-editing: apply errors at different severity levels, preserve meaning, and match context. However there is an internal inconsistency: Rule 1 ('Never break meaning') conflicts with some examples (autocorrect disasters, skipped words, 'massage' vs 'manager') that could change intent or introduce harmful misunderstandings. Also suggestions like 'send as multiple messages' simulate interaction behavior but do not require extra system access.
Install Mechanism
No install spec and no code files — lowest risk. Nothing will be downloaded or executed on disk by the skill itself.
Credentials
No environment variables, credentials, or config paths are requested. The skill does not ask for unrelated secrets or system access.
Persistence & Privilege
always is false and the skill does not request persistent system presence or modify other skills. Autonomous invocation is allowed by default (platform default) but is not excessive here.
Assessment
This skill appears to do what it says: deliberately add human-like imperfections to text. It does not request credentials or install code, which reduces technical risk. Two practical cautions: (1) test outputs before sending in sensitive contexts (legal, medical, security) because some recommended 'errors' could change meaning or produce embarrassing/unsafe results; (2) be mindful of misuse — making text more deceptive is a feature that can enable social-engineering. If you install it, try it on non-sensitive drafts first and review carefully (especially Level 3 outputs). If you need guarantees that meaning never changes, this skill's examples show that guarantee may be hard to achieve in practice.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.