humanizer

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

1.09x

Quality

73%

Does it follow best practices?

Impact

100%

1.09x

Average score across 3 eval scenarios

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./prompts/humanizer/SKILL.md

Quality

Content

63%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A thorough, well-structured catalog of AI-writing patterns with concrete before/after examples that make it highly actionable. Its main weaknesses are length/verbosity across 24 near-parallel sections and a single-file monolithic structure that forgoes progressive disclosure via reference files.

Suggestions

Move the bulk of the 24-pattern catalog into a references file (e.g. PATTERNS.md) and keep SKILL.md as an overview with a short quick-start and a pointer, improving token efficiency and navigation.

Tighten repetitive pattern sections: each already follows the same structure, so the prose explanations can be shortened once the format is established.

Add an explicit verification checkpoint in the Process section (e.g. 're-read aloud and confirm no listed trigger words remain') to strengthen the feedback loop.

Dimension	Reasoning	Score
Conciseness	The document is comprehensive but lengthy (~420 lines) with many before/after blocks that, while illustrative, repeat the same core instruction across 24 patterns; some explanatory prose ('LLMs use statistical algorithms...', the full soul/voice section) could be trimmed. It is mostly efficient but could be tightened.	3 / 5
Actionability	Each pattern gives concrete 'Words to watch', a stated problem, and concrete before/after rewrites that model executable fixes, with minor gaps where no explicit word list is given (e.g. negative parallelisms, rule of three).	4 / 5
Workflow Clarity	A clear sequenced 'Process' section (read, identify, rewrite, verify naturalness, present) with verification criteria, though the validation is qualitative ('sounds natural when read aloud') rather than a hard checkpoint, and the skill is non-destructive so the destructive/batch cap does not apply.	4 / 5
Progressive Disclosure	Content is well-organized by section headings but everything is inlined into a single monolithic SKILL.md with no bundle files or one-level-deep references; the large pattern catalog could be split into a separate reference file for easier navigation.	3 / 5
	Total	14 / 20 Passed

Description

83%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, third-person description that clearly states both the skill's function and its use conditions, anchored to a named source (Wikipedia's 'Signs of AI writing'). It enumerates concrete patterns, making it largely comprehensive and distinct, with only minor keyword-coverage gaps.

Suggestions

Add common synonyms users might say, e.g. 'de-AI text', 'AI-sounding writing', or 'humanize text', to broaden natural trigger coverage.

Tighten the trigger clause by specifying a domain ('Use when editing prose...') to reduce minor overlap with general editing skills.

Dimension	Reasoning	Score
Specificity	Lists several concrete actions ('Detects and fixes patterns', 'Remove signs of AI-generated writing') and enumerates the specific pattern categories (inflated symbolism, promotional language, rule of three, etc.), with only minor gaps in coverage of how fixes are applied.	4 / 5
Completeness	Explicitly answers both 'what' (remove signs of AI-generated writing, detect and fix named patterns) and 'when' ('Use when editing or reviewing text to make it sound more natural and human-written') with concrete trigger phrasing.	5 / 5
Trigger Term Quality	Includes natural phrases users would say ('editing or reviewing text', 'make it sound more natural and human-written') alongside the domain term 'AI-generated writing', though it omits common synonyms like 'AI-sounding' or 'de-AI'.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche (AI-writing-pattern detection/removal) with distinct triggers, though the broad framing of 'editing or reviewing text' could create minor overlap with general editing skills.	4 / 5
	Total	17 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: jdrhyne/agent-skills
Path: prompts/humanizer/SKILL.md
Commit: 439cd3a

Reviewed: 2 days ago

Table of Contents

Discovery Implementation Validation

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