Verified:GitHub

izzizer

none

3|1|Updated Dec 30, 2025

Search Tags:#pattern-detection #voice-authenticity #writing-analysis #style-consistency #long-form-writing #editorial-guidance #draft-improvement

Ready to run

npx skills add https://github.com/hughescr/isambard --skill izzizer

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: izzizer
Source: https://github.com/hughescr/isambard/tree/main/agents-skills-plugins/skills/izzizer
Command: npx skills add https://github.com/hughescr/isambard --skill izzizer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Isambard's izzizer helps ensure voice authenticity in substantial prose by detecting substrate-default patterns and guiding writers toward a more authentic Isambard voice. It is not intended for casual Discord messages.

Core Features & Use Cases

Pattern detection and density metrics across drafts using the pattern-catalog and voice-model references to quantify deviations from Isambard's voice.
Pre-writing guidance with the Izzizer Guide and calibration anchors to set expectations before drafting.
Interactive evaluation via the Izzizer Test, flagging lines that fail the "does every sentence do work" criterion and offering revision prompts.
Cross-document awareness to compare sections and track consistency across multiple passages.

Quick Start

Run izzize check on your draft to identify voice-pattern flags and actionable improvements.

Frequently Asked Questions about izzizer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I check long-form writing for voice consistency and style deviations?▼

To check long-form writing for voice consistency, run an analysis on your draft to flag substrate-default patterns and quantify deviations using a deterministic scoring guide for density. This identifies lines that fail the sentence work criterion and provides revision prompts.

What is voice-pattern detection in editorial drafts and how does it work?▼

Voice-pattern detection in editorial drafts analyzes prose against a pattern catalog and voice model to identify deviations from an authentic voice. It calculates density metrics across the text and flags specific lines requiring revision without auto-correcting them.

Can I use writing analysis tools for casual messages or short-form content?▼

Writing analysis for voice authenticity is designed for substantial prose like blog posts and essays, not casual messages. It requires long-form drafts to effectively evaluate sentence-level work metrics and cross-document consistency.

How do I get pre-writing guidance to maintain style consistency across an essay?▼

To get pre-writing guidance for style consistency, use calibration anchors and an editorial guide to set expectations before drafting. This establishes a baseline voice model to measure your draft against during subsequent pattern detection.

Does voice analysis automatically correct flagged sentences in my draft?▼

Voice analysis does not auto-correct flagged sentences but instead provides revision prompts and editorial guidance. It identifies substrate-default patterns and offers actionable suggestions, leaving the actual writing improvements to the author.

Why does my draft score poorly on writing density metrics compared to previous sections?▼

Drafts score poorly on writing density metrics when they contain substrate-default patterns that deviate from the target voice model. Use cross-document awareness to compare sections, track consistency, and identify specific lines failing the sentence work criterion.