Humanize
SkillDev toolsRewrite AI-generated developer text to sound human — fix inflated language, filler, tautological docs, and robotic tone. Use after review-ai-writing identifies issues.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Humanize skill
What this skill tells your AI
The instructions your AI receives, as published by existential-birds/beagle in plugins/beagle-docs/skills/humanize-beagle/SKILL.md and read by ahel’s review.
Apply fixes from a previous review-ai-writing run with automatic safe/risky classification. Builds on the writing principles in docs-style.
Usage
Invoke the humanize-beagle skill with optional flags: humanize-beagle [--dry-run] [--all] [--category <name>].
Flags:
--dry-run- Show what would be fixed without changing files--all- Fix entire codebase (runs review with --all first)--category <name>- Only fix specific category:content|vocabulary|formatting|communication|filler|code_docs
Instructions
Hard gates
Advance past destructive or evidence-bound steps only when each PASS is true (commands and artifacts—not “I checked mentally”):
- G1 — Safe to edit files — PASS:
git status --porcelainis empty, orgit stash push -u -m "beagle-docs: pre-humanize backup"exits 0. - G2 — Review input is real JSON with expected shape — PASS:
.beagle/ai-writing-review.jsonexists and the file parses as JSON with agit_headkey and afindingsvalue that is an array (possibly empty). Use thejq -ecommand in step 3, or the same checks withjson.loadin Python. If this fails, stop with a parse/validation error—do not apply fixes. - G3 — References before rewrites — PASS: For each finding you will edit, the
references/*.mdfiles required by step 4 for that category/type are read in this session before you change text. - G4 — Per-file validation — PASS: Every modified file passes the step 8 check for its type; otherwise run
git checkout -- "$file"for that file and do not list it as OK in the summary. - G5 — Delete review file only on full success — PASS: Run
rm .beagle/ai-writing-review.jsononly when G4 holds for all files you are keeping unchanged from validation failures (aligns with step 10).
1. Parse Arguments
Extract flags from $ARGUMENTS:
--dry-run- Preview mode only--all- Full codebase scan--category <name>- Filter to specific category
2. Pre-flight Safety Checks
# Check for uncommitted changes
git status --porcelain
If working directory is dirty, warn:
Warning: You have uncommitted changes. Creating a git stash before proceeding.
Run `git stash pop` to restore if needed.
Create stash if dirty:
git stash push -u -m "beagle-docs: pre-humanize backup"
G1 PASS: Either the working tree was already clean, or the stash command exited 0.
3. Load Review Results
Check for existing review file:
cat .beagle/ai-writing-review.json 2>/dev/null
If file missing:
- If
--allflag: Invoke the review-ai-writing skill with--allfirst - Otherwise: Fail with: "No review results found. Invoke the review-ai-writing skill first."
If file exists, validate JSON and freshness (G2):
# Required shape: parseable JSON with git_head and findings array (may be empty)
jq -e 'has("git_head") and ((.findings // []) | type == "array")' .beagle/ai-writing-review.json >/dev/null 2>&1 \
|| { echo "Invalid or incompatible ai-writing-review.json"; exit 1; }
# Get stored git HEAD from JSON
stored_head=$(jq -r '.git_head' .beagle/ai-writing-review.json)
current_head=$(git rev-parse HEAD)
if [ "$stored_head" != "$current_head" ]; then
echo "Warning: Review was run at commit $stored_head, but HEAD is now $current_head"
fi
If stale, prompt: "Review results are stale. Re-run review? (y/n)"
4. Load Reference Material
Read the appropriate reference files based on the findings being fixed:
- Read
references/vocabulary-swaps.mdwhen applyingai_vocabulary_highorai_vocabulary_lowfixes - Read
references/fix-strategies.mdfor strategy details and before/after examples for any category - Read
references/developer-voice.mdfor tone/register guidance when rewriting prose
Only load what you need — if fixing only vocabulary, skip the voice guide.
5. Filter Findings
If --category is set, filter findings to that category only.
Partition remaining findings by fix_safety:
Safe Fixes (auto-apply):
chat_leak- Delete conversational artifactscutoff_disclaimer- Delete knowledge cutoff referencesfiller_phrase- Delete filler phrasesheading_restatement- Delete restating first sentenceemoji_decoration- Remove emoji from technical textboldface_overuse- Remove excessive bold formattingai_vocabulary_high- Swap high-signal AI wordsnarrating_obvious- Delete obvious code commentssynthetic_opener- Delete "In today's..." openerssycophantic_tone- Delete or neutralize praisevague_authority- Delete unattributed claimsexcessive_hedging- Remove qualifiersgeneric_conclusion- Delete summary paddingcopula_avoidance- Use "is/are" naturallyrhetorical_device- Delete rhetorical questionsem_dash_overuse- Replace formulaic em dashes with commas, parentheses, or colonsthematic_break- Remove horizontal rules before headingstitle_case_heading- Convert AI title-case headings to sentence casecurly_quotes- Normalize curly quotes/apostrophes to straightnegative_parallelism- Delete "Not just X, but also Y" filler constructionschallenges_and_prospects- Delete "Despite its... faces challenges..." formulaic wrappers
Needs Review Fixes (require confirmation):
promotional_language- Rewrite with specificsformulaic_structure- Restructure sectionssynonym_cycling- Pick consistent termcommit_inflation- Rewrite commit scopetautological_docstring- Rewrite or delete docstringexhaustive_enumeration- Trim parameter docsthis_noun_verbs- Rewrite docstring voiceai_vocabulary_low- Reduce cluster densityapologetic_error- Rewrite error messagerule_of_three- Simplify three-item lists used as filler comprehensivenessinline_header_list- Restructure boldfaced inline-header vertical listsunnecessary_table- Convert small tables to proseregression_to_mean- Restore specific facts replaced by vague praise
6. Apply Safe Fixes
If --dry-run:
## Safe Fixes (would apply automatically)
| # | File | Line | Type | Action |
|---|------|------|------|--------|
| 1 | README.md | 3 | synthetic_opener | Delete "In today's rapidly evolving..." |
| 2 | src/auth.py | 15 | narrating_obvious | Delete "# Check if user exists" |
| 3 | README.md | 42 | ai_vocabulary_high | Replace "utilize" with "use" |
...
Otherwise, apply fixes grouped by file to minimize file I/O:
- Sort findings by file, then by line number (descending, to avoid offset drift)
- For each file, apply all safe fixes in reverse line order
- For git artifacts (
git:commit:*,git:pr:*), skip — these can't be auto-fixed. Report them for manual attention.
7. Handle Needs Review Fixes
If --dry-run, list them:
## Needs Review Fixes (would prompt interactively)
| # | File | Line | Type | Original | Suggested |
|---|------|------|------|----------|-----------|
| 4 | README.md | 8 | promotional_language | "powerful, enterprise-grade solution" | "authentication library" |
...
Otherwise, for each fix, prompt interactively:
[README.md:8] Promotional language: "powerful, enterprise-grade solution"
Suggested: "authentication library"
(y)es / (n)o / (e)dit / (s)kip all:
Track user choices:
y- Apply this fix as suggestedn- Skip this fixe- User provides custom replacements- Skip all remaining interactive fixes
8. Validate Results
For each modified markdown file, verify basic validity:
# Check for broken markdown (unclosed code blocks, broken links)
# Simple check: matching ``` pairs
grep -c '```' "$file" | awk '{print ($1 % 2 == 0) ? "OK" : "WARNING: odd number of code fences"}'
For modified source files, check syntax is still valid:
Python:
python3 -c "import ast; ast.parse(open('$file').read())"
TypeScript/JavaScript:
npx -y acorn --ecma2020 "$file" > /dev/null 2>&1
If validation fails for any file, revert that file:
git checkout -- "$file"
echo "Reverted $file due to validation failure"
9. Report Results
## Humanize Summary
### Applied Fixes
- [x] README.md:3 - Deleted synthetic opener
- [x] README.md:42 - Replaced "utilize" with "use"
- [x] src/auth.py:15 - Deleted obvious comment
### Interactive Fixes
- [x] README.md:8 - Rewrote promotional language (user approved)
- [ ] docs/guide.md:22 - Skipped by user
### Skipped (Git Artifacts)
- [ ] git:commit:abc1234 - Chat leak in commit message (amend manually)
### Validation
- README.md: OK
- src/auth.py: OK
### Diff Summary
git diff --stat
10. Cleanup
On successful completion (all validations pass):
rm .beagle/ai-writing-review.json
If any validation fails, keep the file and report:
Review file preserved at .beagle/ai-writing-review.json
Fix issues and re-run, or restore with: git stash pop
Core Principles
- Delete first, rewrite second. Most AI patterns are padding. Removing them improves the text.
- Use simple words. Replace "utilize" with "use", "facilitate" with "help", "implement" with "add".
- Keep sentences short. Break compound sentences. One idea per sentence.
- Preserve meaning. Never change what the text says, only how it says it.
- Match the register. Commit messages are terse. READMEs are conversational. API docs are precise. Read
references/developer-voice.mdfor the full register guide. - Don't overcorrect. A slightly formal sentence is fine. Only fix patterns that read as obviously AI-generated.
- Understand regression to the mean. LLMs produce the most statistically likely output. Specific, unusual facts get replaced with generic, positive descriptions. When humanizing, restore specificity — replace vague praise with concrete details.
- Score density, not individual words. AI vocabulary words co-occur. One or two may be coincidental; a cluster of 3+ is a strong AI tell.
Example
Invoke the humanize-beagle skill with flags:
--dry-run— preview all fixes without applying--category vocabulary— fix only vocabulary issues--all— full codebase scan and fix--category filler --dry-run— preview filler fixes only
Rules
- Always load reference material before applying fixes (step 4); satisfy G3 per finding
- Never modify files without a clean working tree or a successful stash (G1)
- Apply safe fixes in reverse line order to avoid offset drift
- Never auto-fix git artifacts (commits, PRs) — report them for manual action
- Validate every modified file before considering it done (G4)
- Revert files that fail validation
- Do not present the step 9 summary as “complete” until step 8 validation has passed for every file you are keeping
- Remove
.beagle/ai-writing-review.jsononly after full success (G5); if validation failed partway, keep the file and follow step 10
Signals
- GitHub stars
- 81
- Forks
- 8
- Last commit
- Aug 2026
Advanced
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humanize-beagle- Source
- github.com/existential-birds/beagle