# Common Overused AI Words Humanizer Targets: Complete List and Detection Logic > Discover common overused AI words like actually crucial delve and tapestry that Humanizer detects and rewrites. Learn how this tool uses pattern 7 to replace high-frequency LLM markers with natural synonyms. - Repository: [Siqi Chen/humanizer](https://github.com/blader/humanizer) - Tags: getting-started - Published: 2026-09-06 --- **Humanizer detects and rewrites 24 specific overused AI words—such as "actually," "crucial," "delve," and "tapestry"—by scanning input text for these high-frequency LLM markers and replacing them with natural synonyms, as defined in pattern #7 of the [`SKILL.md`](https://github.com/blader/humanizer/blob/main/SKILL.md) configuration.** The **blader/humanizer** repository is a Markdown-based skill designed to clean AI-generated prose by applying 35 well-defined patterns derived from Wikipedia's *Signs of AI writing*. Among these detection rules, the targeting of common overused AI words serves as a critical filter to eliminate the inflated, generic diction typical of large language model outputs. ## What Are Overused AI Words? In the Humanizer framework, **overused AI words** constitute pattern #7, a curated lexicon of terms that LLMs statistically overuse compared to human writers. These words often sound formal but contribute little semantic value, creating prose that feels artificially "AI-like." The complete list is hardcoded in [[`SKILL.md`](https://github.com/blader/humanizer/blob/main/SKILL.md)](https://github.com/blader/humanizer/blob/main/SKILL.md#L12-L15) and cross-referenced in the pattern table at [[`README.md`](https://github.com/blader/humanizer/blob/main/README.md)](https://github.com/blader/humanizer/blob/main/README.md#L70-L73). ### The Complete Inventory of Target Terms Humanizer flags the following vocabulary for automatic rewriting: - **actually** - **additionally** - **align with** - **crucial** - **delve** - **emphasizing** - **enduring** - **enhance** - **fostering** - **garner** - **gate / gated / gating** *(figurative use only)* - **highlight** *(verb)* - **interplay** - **intricate / intricacies** - **key** *(adjective)* - **landscape** *(abstract noun)* - **pivotal** - **quietly** - **showcase** - **tapestry** *(abstract noun)* - **testament** - **underscore** *(verb)* - **valuable** - **vibrant** When Humanizer encounters any of these terms, it treats them as **AI-telling signals** that require neutralization through synonym replacement or deletion. ## How Humanizer Detects and Rewrites These Words According to the source code in [`SKILL.md`](https://github.com/blader/humanizer/blob/main/SKILL.md), the detection engine follows a strict three-phase process: 1. **Scanning**: The input text is parsed for any occurrence of the 24 target words defined in pattern #7. 2. **Marking**: Each match is flagged as an AI-telling signal, indicating the prose may be machine-generated. 3. **Rewriting**: The system reconstructs the sentence using tighter, more natural wording—such as converting *"actually"* to *"in fact"* or *"additionally"* to *"also"*—while preserving factual accuracy. This logic ensures that the output retains the original meaning but eliminates the stylistic fingerprints common to LLM drafts. ## Practical Usage Examples ### Markdown Prompt Workflow You can invoke Humanizer directly within supported agents like Claude using the skill syntax: ```markdown # Prompt (as you would in Claude or any agent supporting skills) /humanizer Please humanize this text: > Actually, the new feature is crucial for improving user experience. Additionally, it aligns with our roadmap and enhances overall performance. # Humanizer's rewrite (automatically produced) The new feature improves user experience and aligns with our roadmap, boosting overall performance. ``` ### CLI Installation To use Humanizer globally across your development environment: ```bash # Install the skill globally npx skills add blader/humanizer --global # Then invoke the skill in any supported agent: /humanizer ``` ## Key Configuration Files Understanding the repository structure helps clarify how the word list is maintained: - **[[`SKILL.md`](https://github.com/blader/humanizer/blob/main/SKILL.md)](https://github.com/blader/humanizer/blob/main/SKILL.md)**: Contains the canonical definition of pattern #7 **Overused AI words** and the precise list of target terms at lines 12-15. - **[[`README.md`](https://github.com/blader/humanizer/blob/main/README.md)](https://github.com/blader/humanizer/blob/main/README.md)**: Summarizes all 35 patterns in a reference table, including the specific entry for pattern #7 at lines 70-73 with usage examples. - **[[`AGENTS.md`](https://github.com/blader/humanizer/blob/main/AGENTS.md)](https://github.com/blader/humanizer/blob/main/AGENTS.md)**: Provides metadata and integration notes for deploying the skill across different AI agents. ## Summary - **Humanizer** targets **24 specific overused AI words** defined in pattern #7 of [`SKILL.md`](https://github.com/blader/humanizer/blob/main/SKILL.md), including terms like *crucial*, *delve*, *intricate*, and *vibrant*. - The detection system **scans, marks, and rewrites** sentences containing these high-frequency LLM markers, replacing them with natural synonyms or removing them entirely. - All target words are **hardcoded at lines 12-15 of [`SKILL.md`](https://github.com/blader/humanizer/blob/main/SKILL.md)** and documented in the README's pattern table for transparency. - The skill operates as a **Markdown-based filter** that can be invoked via CLI (`npx skills add blader/humanizer`) or directly within supported agents using the `/humanizer` command. ## Frequently Asked Questions ### What are the most common overused AI words Humanizer detects? The most frequently flagged terms include **"actually,"** **"crucial,"** **"delve,"** **"enhance,"** and **"vibrant."** According to the [`SKILL.md`](https://github.com/blader/humanizer/blob/main/SKILL.md) configuration, these words appear disproportionately in LLM outputs compared to human writing and are prioritized for replacement with simpler alternatives. ### How does Humanizer decide which words to replace? Humanizer references a **static allowlist of 24 terms** defined in pattern #7. When the parser encounters any word on this list—such as *garner*, *tapestry*, or *underscore*—it automatically triggers the rewriting pipeline to substitute the term with a more natural equivalent or eliminate it if it adds no semantic value. ### Can I customize the list of overused words in Humanizer? The current implementation in [[`SKILL.md`](https://github.com/blader/humanizer/blob/main/SKILL.md)](https://github.com/blader/humanizer/blob/main/SKILL.md#L12-L15) uses a **fixed vocabulary list** hardcoded into pattern #7. To modify the target words, you would need to fork the repository and edit the word definitions directly in the skill configuration, as the tool does not expose runtime customization parameters for this specific pattern. ### Where does Humanizer get its list of AI-writing patterns? The 35 detection patterns—including the overused words list—are derived from **Wikipedia's *Signs of AI writing*** article. This source provides the empirical basis for identifying linguistic markers that statistically differentiate LLM-generated text from human prose, as implemented across the [`SKILL.md`](https://github.com/blader/humanizer/blob/main/SKILL.md) and [`README.md`](https://github.com/blader/humanizer/blob/main/README.md) documentation files.