| name | unslop |
| description | Use this skill when you need to run the unslop repo, analyze a domain for repetitive AI defaults, generate a reusable skill file, and verify that the output is specific and materially different from the baseline. |
unslop
Use this repo to generate a domain-specific profile that removes repetitive AI defaults.
Workflow
- Clone
https://github.com/mshumer/unslop if the repo is not already present.
- Enter the repo root and use a Python virtual environment.
- Decide whether the job is
text or visual.
Text: writing, emails, essays, tutorials, copy, code explanations.
Visual: websites, landing pages, HTML pages, UI mockups.
- Install Playwright only for visual runs:
pip install playwright && playwright install chromium
- Run the tool:
python3 unslop.py --domain "<domain>"
python3 unslop.py --domain "<domain>" --type visual --count 20 --concurrency 3
Output Review
Check unslop-output/analysis.md and unslop-output/skill.md.
analysis.md must be concrete, counted, and specific.skill.md should mostly say what to avoid, not prescribe one new stock style.- For visual runs, compare
unslop-output/before-after/before.html and unslop-output/before-after/after.html.
- The
after result should feel meaningfully less generic than before.
If the analysis is thin or obviously missed repeated patterns, rerun or rewrite the analysis from inside unslop-output after reviewing the screenshots and sample files directly.
Deliverable
Return:
- The generated
skill.md
- The main repeated patterns the analysis found
- Any caveats about sample quality, missing screenshots, or weak comparison output
