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Ai Writing Humanizer

v0.1.0

Automatically strip AI writing patterns and stock phrases from user-facing prose before sending. Use when preparing longer texts to ensure a natural, human t...

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byHost Hobbit@hosthobbit
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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Benign
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Benign
high confidence
✓
Purpose & Capability
Name/description match the delivered artifacts: a small Python script plus reference and tests implement regex-based humanization. No unrelated binaries, env vars, or install steps are requested, so the capability is proportional to the stated purpose.
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Instruction Scope
SKILL.md instructs local use (CLI or import) and to 'load automatically for any user-facing prose longer than ~150 words.' The runtime instructions do not read external files or env vars beyond the explicit input file, nor do they send data outside. However, the automatic-loading instruction and the script's aggressive pattern removals (e.g., removing all occurrences of 'was', 'were', 'has been') could unintentionally change meaning or act on sensitive content without explicit consent — consider limiting auto-invoke or requiring explicit confirmation for sensitive texts.
✓
Install Mechanism
No install spec (instruction-only plus bundled scripts). No downloads or external installers — code is provided in the bundle and runs locally, which is low risk from an install perspective.
✓
Credentials
No environment variables, credentials, or config paths are requested. The skill does not attempt to access unrelated secrets or system configuration.
✓
Persistence & Privilege
always is false and the skill doesn't modify other skills or system-wide settings. It can be invoked autonomously by the agent (platform default), but no elevated persistence or cross-skill config changes are requested.
Assessment
This skill appears to do what it says and runs locally with no network or secret access. Before installing, review whether you want it to be auto-invoked on longer user-facing text (it may process content you didn't intend it to). Also inspect and test the regex behavior on representative texts — the script removes simple tokens like 'was' and 'were' which can change meaning or break grammar. If you handle sensitive or legal text, require explicit invocation and run tests to ensure the transformations are acceptable.

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.
Termshttps://spdx.org/licenses/MIT-0.html

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