What is the 'Problem-First' opening approach?

Instead of starting with a definition, it drops the reader into a specific technical scenario where they encounter a problem, making the documentation immediately relatable and useful.

Does this skill help with README maintenance?

Yes, by focusing on high-level design principles and 'why' decisions rather than listing every file, it creates documentation that stays relevant longer and is easier to maintain.

Can I use this for both internal and public documentation?

Absolutely. It supports both 'Instructional' voice for patterns/guides and 'Narrative' voice for retrospectives and experience reports.

How does this skill avoid the 'AI-generated feel'?

It specifically bans common LLM patterns like excessive bolding, marketing buzzwords (e.g., 'revolutionary', 'seamless'), and rigid bullet-point structures, replacing them with narrative flow and specific data.

Human-Centric Documentation & READMEs

Name: Human-Centric Documentation & READMEs
Author: EpicenterHQ

byEpicenterHQ

•

3,817

Content Management

Crafts authentic, non-AI-sounding technical documentation and READMEs using human-centric writing principles and structural patterns.

About

This skill equips Claude with the specific voice and structural guidelines necessary to produce high-quality technical content that feels written by a person, not a machine. It focuses on removing common AI writing artifacts—such as excessive bolding, corporate jargon, and repetitive bullet lists—in favor of narrative-driven problem solving, specific numbers, and concrete code comparisons. By prioritizing the 'why' over the 'what,' it helps developers create READMEs and articles that explain architectural decisions and design trade-offs while maintaining a conversational, peer-to-peer tone.

Key Features

Implements structured comparison blocks (❌/✅) and trade-off tables.
3,817 GitHub stars
Eliminates AI artifacts like 'space-hyphen-space' and corporate marketing speak.
Converts generic feature lists into cohesive, flowing narrative prose.
Enforces a 'Problem-First' opening structure for technical articles.
Prioritizes design reasoning and architectural 'why' in project READMEs.

Use Cases

Rewriting robotic, AI-generated technical posts into authentic human-sounding articles.
Creating READMEs that focus on project principles and architectural decisions instead of file lists.
Standardizing punctuation and formatting across a project's documentation suite.

About

Key Features

Implements structured comparison blocks (❌/✅) and trade-off tables.
3,817 GitHub stars
Eliminates AI artifacts like 'space-hyphen-space' and corporate marketing speak.
Converts generic feature lists into cohesive, flowing narrative prose.
Enforces a 'Problem-First' opening structure for technical articles.
Prioritizes design reasoning and architectural 'why' in project READMEs.

Use Cases

Rewriting robotic, AI-generated technical posts into authentic human-sounding articles.
Creating READMEs that focus on project principles and architectural decisions instead of file lists.
Standardizing punctuation and formatting across a project's documentation suite.