avav25/humanizer
.agents/skills/humanizer/SKILL.md
Remove signs of AI-generated writing from text. Use when editing, reviewing, or producing any public-facing text — blog posts, social media, UI copy, emails, landing pages, documentation. Detects and fixes AI patterns including inflated symbolism, promotional language, vague attributions, em dash overuse, rule of three, AI vocabulary, negative parallelisms, sycophantic tone, and filler phrases.
testing
Updated Apr 16, 2026
$ install --global
skillsauthnpx skillsauth add avav25/ai-assets humanizerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 24, 2026, 8:49 PM1.9s1 file scanned
SKILL.md
- name:
- humanizer
- description:
- Remove signs of AI-generated writing from text. Use when editing, reviewing, or producing any public-facing text — blog posts, social media, UI copy, emails, landing pages, documentation. Detects and fixes AI patterns including inflated symbolism, promotional language, vague attributions, em dash overuse, rule of three, AI vocabulary, negative parallelisms, sycophantic tone, and filler phrases.
- user-invocable:
- true
Humanizer
Identifies and removes signs of AI-generated text. Makes writing sound natural and human. Based on Wikipedia's "Signs of AI writing" guide maintained by WikiProject AI Cleanup.
When to Use
- Writing or editing blog posts, social media posts, emails, landing pages
- Writing UI copy, microcopy, error messages, onboarding text
- Reviewing any text before publication
- Any content that will be read by humans outside the team
Process
- Identify AI patterns — scan for the patterns listed below
- Rewrite problematic sections — replace AI-isms with natural alternatives
- Preserve meaning — keep the core message intact
- Maintain voice — match the intended tone (formal, casual, technical)
- Add soul — inject actual personality, not just remove bad patterns
- Anti-AI audit — ask "What makes this obviously AI generated?", list remaining tells, then revise
Adding Soul
Avoiding AI patterns is half the job. Sterile, voiceless writing is just as obvious.
Signs of soulless writing:
- Every sentence same length and structure
- No opinions, just neutral reporting
- No uncertainty or mixed feelings acknowledged
- No first-person perspective when appropriate
- No humor, edge, or personality
How to fix:
- Have opinions — react to facts, do not just report them
- Vary rhythm — short punchy sentences mixed with longer ones
- Acknowledge complexity — "impressive but unsettling" beats "impressive"
- Use "I" when it fits — first person is honest, not unprofessional
- Let some mess in — tangents and asides are human
- Be specific about feelings — not "concerning" but "unsettling that agents churn away at 3am"
See ai-writing-patterns.md for the full pattern catalog with before/after examples.
Quick Reference — Pattern Categories
| # | Pattern | Signal Words | |---|---|---| | 1 | Inflated significance | stands as, testament, pivotal, vital role, broader, indelible mark | | 2 | Notability inflation | independent coverage, active social media presence | | 3 | Superficial -ing phrases | highlighting, ensuring, reflecting, symbolizing, showcasing | | 4 | Promotional language | boasts, vibrant, profound, nestled, groundbreaking, renowned, stunning | | 5 | Vague attributions | experts argue, industry reports, some critics | | 6 | Formulaic challenges sections | despite challenges... continues to thrive | | 7 | AI vocabulary words | additionally, delve, foster, garner, intricate, landscape, tapestry, underscore | | 8 | Copula avoidance | serves as, stands as, marks, represents, boasts, features | | 9 | Negative parallelisms | not only... but, not just about... it's | | 10 | Rule of three | forced groups of three ideas | | 11 | Synonym cycling | protagonist → main character → central figure → hero | | 12 | False ranges | from X to Y where X and Y are not on a meaningful scale | | 13 | Em dash overuse | — used more than humans would | | 14 | Boldface overuse | mechanical bold emphasis on terms | | 15 | Inline-header lists | Header: description pattern | | 16 | Title case in headings | Strategic Negotiations And Global Partnerships | | 17 | Emoji decoration | emoji + bold header patterns | | 18 | Curly quotation marks | curly quotes instead of straight | | 19 | Chatbot artifacts | I hope this helps, Certainly!, Would you like... | | 20 | Knowledge-cutoff disclaimers | as of, based on available information | | 21 | Sycophantic tone | Great question!, You're absolutely right! | | 22 | Filler phrases | in order to, due to the fact that, it is important to note | | 23 | Excessive hedging | could potentially possibly be argued | | 24 | Generic positive conclusions | the future looks bright, exciting times | | 25 | Hyphenated word pair overuse | cross-functional, data-driven, high-quality used uniformly |
Output Format
When humanizing text, provide:
- Draft rewrite — cleaned version
- AI tells audit — brief bullets listing remaining AI signals
- Final rewrite — revised after the audit
- Changes summary — what was fixed (optional, if helpful)
Integration
- Rule:
humanize-contentrule auto-activates this skill for all public-facing content - Used by workflows:
blog-postskill (step 4.5),marketingskill (all content operations),docsskill (public-facing content) - Used by skill:
content-creation(Gate 7: Humanization) - Companion resource:
ai-writing-patterns.md(full pattern catalog with examples)
Related Skills
avav25/knowledge-sync
development
VerifiedTrustedCommunity
Use this skill when running the recurring (daily) knowledge-base rescan for a repo that already has knowledge/.knowledge-sync.yml — the main-thread dispatcher that reads the config, computes the git delta since last_scanned_sha, maps changed paths to affected doc areas, early-exits cheaply when nothing changed, then fans out one Agent(content-writer) per affected area, applies the propose/direct update policy, advances the baseline only on success, and writes an L4 run log — all with the G1 untrusted-content choke-point, secret-scan, deny-list, and budget controls woven in. For first-time setup use /knowledge-sync-init.
1SKILL.mdUpdated May 24, 2026
avav25/knowledge-sync-init
development
VerifiedTrustedCommunity
Use this skill when bootstrapping scheduled knowledge-base sync for a repo that has no knowledge/.knowledge-sync.yml yet — to run one-time setup that detects the knowledge_root from CLAUDE.md/AGENTS.md, maps doc areas to source globs, records opt-in external sources (Linear/Notion/WebFetch, all disabled by default), captures a baseline last_scanned_sha, sets the per-area update policy, generates or seeds knowledge/CONVENTIONS.md, provisions the L4 memory dir, and offers to register the daily routine. Routes ongoing recurring sync operations to /knowledge-sync.
1SKILL.mdUpdated May 24, 2026
avav25/ai-skills-init
tools
VerifiedTrustedCommunity
Use this skill when bootstrapping a target repository to be ai-skills-aware — on the first run of any ai-skills workflow in a fresh repo, when adopting the ai-skills plugin in an existing repo, or after upgrading to a plugin version that adds new memory paths or templates, including when the user does not say "init" but asks to "set up" or "onboard" the repo — to detect codebase type, create CLAUDE.md + AGENTS.md scaffolding, initialize the .ai-skills-memory/ directory tree from L1 templates, and configure .gitignore. Idempotent — safe to re-run. Accepts `--codebase-type <type>` and `--overwrite`. Not for re-initializing only memory — use `/memory-init` instead.
1SKILL.mdUpdated May 18, 2026
avav25/plugin-author
tools
VerifiedTrustedCommunity
Use this skill when extending, repairing, or improving plugin assets, when ingesting a `/feedback` report as a fix-cycle backlog, or when you do not remember which lower-level command is right for the job — the umbrella workflow for ai-skills plugin-asset authoring and maintenance: creating, auditing, fixing, improving, refactoring, and migrating skills, agents, rules, hooks, prompts, schemas, and rubrics inside the plugin. Auto-classifies the request, loads the right knowledge skills (`@prompt-engineering`, `@context-engineering`, `@team-protocols`), and spawns the right subagents (`prompt-engineer`, `system-architect`, `python-engineer`, `software-engineer`, `qa-engineer`, `eval-judge`) via the `Agent` tool.
1SKILL.mdUpdated May 14, 2026