skills/simplify/SKILL.md
Use when you need to detect or remove AI slop from text — filler openers, hedge stacks, redundant qualifiers, and emoji clusters. Scans stdin or a file and optionally rewrites clean output.
npx skillsauth add seokan-jeong/team-shinchan team-shinchan:simplifyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Removes AI-generated filler language from text files or stdin.
# Scan mode (default) — print matched slop phrases with line numbers
echo "Certainly, here is your answer." | node ${CLAUDE_PLUGIN_ROOT}/src/slop-cleaner.js
# Fix mode — rewrite cleaned text to stdout
echo "Certainly, here is your answer." | node ${CLAUDE_PLUGIN_ROOT}/src/slop-cleaner.js --fix
# File input — scan a file
node ${CLAUDE_PLUGIN_ROOT}/src/slop-cleaner.js --file path/to/doc.md
# File input + fix — rewrite cleaned text back to the file
node ${CLAUDE_PLUGIN_ROOT}/src/slop-cleaner.js --fix --file path/to/doc.md
| Category | Examples | |----------|---------| | Filler openers | "Certainly,", "Absolutely,", "Of course,", "Sure,", "Great,", "I'll help you" | | Hedge stacks | "It's worth noting that ", "It is important to mention ", "Please note that " | | Redundant qualifiers | "very unique" → "unique", "completely eliminate" → "eliminate", "totally unnecessary" → "unnecessary" | | Emoji clusters | 3 or more consecutive emoji in a row |
When this skill is invoked, run the slop-cleaner script directly using the Bash tool:
# Scan mode
node ${CLAUDE_PLUGIN_ROOT}/src/slop-cleaner.js --file <path>
# Fix mode
node ${CLAUDE_PLUGIN_ROOT}/src/slop-cleaner.js --fix --file <path>
Report the output to the user. If slop is found in scan mode, summarize the matches and suggest running with --fix to clean them.
development
Deterministic adversarial code review for high-stakes scope — independent per-dimension review, a non-skippable per-finding refutation, a completeness critic, and a schema-validated rubric judge. Opt-in main-loop Workflow tier.
data-ai
Deterministic loop-until-done for high-stakes long-running tasks — a worker/verifier loop the script bounds by iteration cap, token budget, and stagnation, closed by an Action-Kamen gate. Opt-in main-loop Workflow tier.
testing
Deterministic adversarial debate for high-stakes or irreversible decisions — mandatory refutation plus a scored judge panel. Opt-in main-loop Workflow tier.
development
Deterministic competitive code tournament — N builders independently solve one task and return patches, an Action-Kamen judge scores them head-to-head, the winner is picked by score and applied. Opt-in main-loop Workflow tier.