/rewrite
Rewrite a draft message, explanation, or note to strip AI voice, slop, and filler while preserving meaning. Use to polish functional prose before sending.
$ npx -y skills add bendrucker/claude --skill rewrite --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/rewrite
Context preview
The summary Claude sees to decide when to auto-load this skill.
Rewrite a draft message, explanation, or note to strip AI voice, slop, and filler while preserving meaning. Use to polish functional prose before sending.
SKILL.md
rewrite.SKILL.mdname: writing:rewrite
description: >-
Rewrite a draft message, explanation, or note to strip AI voice, slop, and
filler while preserving meaning. Use to polish functional prose before
sending.
argument-hint: "[file path or text; omit to read input from the clipboard]"
user-invocable: true
context: fork
background: false
allowed-tools:
- Bash
- Read
- Skill
Rewrite
Load the `writing:writing` skill for the style rules, then rewrite the input to match them. Preserve all functional information. Change only voice, word choice, and sentence structure, conveying the same information in fewer, clearer words.
When the input is the user's own writing rather than model output, name its core point and a few voice signals before editing: vocabulary, cadence, bluntness, humor, admitted uncertainty, digressions. Keep that note to yourself and make the smallest edit that clears the tells. Stripping the voice is the goal only when the voice is a model's.
These rules apply on top of that skill:
- Specific verbs over vague ones. "Generates a report" not "handles report generation."
- No marketing language.
- No excessive enthusiasm.
Input
$ARGUMENTS
If `$ARGUMENTS` is a path to an existing file, read the file. Otherwise treat it as the text itself. If empty, ask for the text to rewrite (you may offer to read it from the clipboard).
Lint
Before and after rewriting, run the scan script in single-input mode to find violations. It accepts a file path, inline text, or stdin and outputs one finding per line (`line:col: category: message`):
bun ${CLAUDE_SKILL_DIR}/../scan/scripts/scan.ts --input path/to/file.mdFix every hard tell (em dash, copula avoidance, hedging, filler, vocabulary, and the other fixed-phrase categories), then re-run until those are clean.
Treat `marketing verb` findings as advisory. The script flags each one, but the live hook only objects when their weighted sum is high enough, so a lone marketing verb may be fine. Consider each in context and replace the ones that read as promotional rather than driving the count to zero.
Check
Once the tells are clean, answer the questions in [`references/check.md`](references/check.md) against the rewrite beside the original. They cover the failures a detector cannot see: invented or dropped claims, cutting out of proportion to the slop, and a distinctive sentence flattened for consistency. Fix what fails and re-check.
Output
Display the rewritten text directly. Do not wrap it in a code block unless the input was code.
Read more
name: writing:rewrite description: >- Rewrite a draft message, explanation, or note to strip AI voice, slop, and filler while preserving meaning. Use to polish functional prose before sending. argument-hint: "[file path or text; omit to read input from the clipboard]" user-invocable: true context: fork background: false allowed-tools: - Bash - Read - Skill
Rewrite
Load the `writing:writing` skill for the style rules, then rewrite the input to match them. Preserve all functional information. Change only voice, word choice, and sentence structure, conveying the same information in fewer, clearer words.
When the input is the user's own writing rather than model output, name its core point and a few voice signals before editing: vocabulary, cadence, bluntness, humor, admitted uncertainty, digressions. Keep that note to yourself and make the smallest edit that clears the tells. Stripping the voice is the goal only when the voice is a model's.
These rules apply on top of that skill:
- Specific verbs over vague ones. "Generates a report" not "handles report generation."
- No marketing language.
- No excessive enthusiasm.
Input
$ARGUMENTS
If `$ARGUMENTS` is a path to an existing file, read the file. Otherwise treat it as the text itself. If empty, ask for the text to rewrite (you may offer to read it from the clipboard).
Lint
Before and after rewriting, run the scan script in single-input mode to find violations. It accepts a file path, inline text, or stdin and outputs one finding per line (`line:col: category: message`):
bun ${CLAUDE_SKILL_DIR}/../scan/scripts/scan.ts --input path/to/file.mdFix every hard tell (em dash, copula avoidance, hedging, filler, vocabulary, and the other fixed-phrase categories), then re-run until those are clean.
Treat `marketing verb` findings as advisory. The script flags each one, but the live hook only objects when their weighted sum is high enough, so a lone marketing verb may be fine. Consider each in context and replace the ones that read as promotional rather than driving the count to zero.
Check
Once the tells are clean, answer the questions in [`references/check.md`](references/check.md) against the rewrite beside the original. They cover the failures a detector cannot see: invented or dropped claims, cutting out of proportion to the slop, and a distinctive sentence flattened for consistency. Fix what fails and re-check.
Output
Display the rewritten text directly. Do not wrap it in a code block unless the input was code.
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Repo: bendrucker/claude
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