How do I install the 905 Feature Order Checker 00999d80 skill?

Run npx skillmds@latest add tools-only/905-feature-order-checker-00999d80 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the 905 Feature Order Checker 00999d80 skill do?

Define requirements for detecting text order violations between PDF and EPUB. It is listed under Docs & Writing on SkillMD.

Is 905 Feature Order Checker 00999d80 safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with 905 Feature Order Checker 00999d80?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is 905 Feature Order Checker 00999d80 free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published 905 Feature Order Checker 00999d80?

tools-only (@tools-only) published this skill. Their other Agent Skills are listed on their SkillMD profile.

905 Feature Order Checker 00999d80 by tools-only

Name: 905 Feature Order Checker 00999d80
Author: tools-only

File contents

Requirements & Problem Understanding

Problem Statement

What problem are we solving?

PDF documents do not store text as a continuous stream but as positioned blocks. Extraction can often result in incorrect reading orders (e.g., mixing columns or skipping to page footers prematurely).
A standard completeness check (presence of text) does not catch these "scrambled" text scenarios.
Users need a guarantee that the book remains readable and the logical flow is preserved.

Goals & Objectives

What do we want to achieve?

Primary Goal: Calculate a numerical order_score representing how well the sequence of text in EPUB follows the sequence in PDF.
Secondary Goal: Identify specific chunks of text that are out of order for debugging.
Non-goal: Automatic fixing of the order (that belongs to the converter and its strategies).

User Stories & Use Cases

How will users interact with the solution?

As a developer, I want to receive an order_score after conversion so I can decide if the result is acceptable.
As a conversion strategy developer, I want to see which chunks are misplaced to identify logic errors in my reading_order detector.
As a user, I want the validation report to fail if the text order is significantly broken (>2% displacement).

Success Criteria

How will we know when we're done?

The system correctly identifies identical sequences as 100% order score.
The system correctly flags swapped paragraphs with a score < 100%.
Definition of Pass: A score >= 98% is considered a successful order validation (allowing for minor noise/shifts).
Performance: Must be able to process a 300-page book in seconds using chunk-based LCS.

Constraints & Assumptions

What limitations do we need to work within?

Assumption: Both PDF and EPUB texts are already canonicalized and segmented into chunks.
Constraint: Must use the text_segmenter outputs to ensure consistency.

Questions & Open Items

What do we still need to clarify?

What is the best mathematical approach for order_score? (LCS vs Kendall Tau distance). Product vision suggests LCS.

---name: 905-feature-order-checker-00999d80description: Define requirements for detecting text order violations between PDF and EPUB.---# Requirements & Problem Understanding## Problem Statement**What problem are we solving?**- PDF documents do not store text as a continuous stream but as positioned blocks. Extraction can often result in incorrect reading orders (e.g., mixing columns or skipping to page footers prematurely). - A standard completeness check (presence of text) does not catch these "scrambled" text scenarios.- Users need a guarantee that the book remains readable and the logical flow is preserved.## Goals & Objectives**What do we want to achieve?**- **Primary Goal:** Calculate a numerical `order_score` representing how well the sequence of text in EPUB follows the sequence in PDF.- **Secondary Goal:** Identify specific chunks of text that are out of order for debugging.- **Non-goal:** Automatic fixing of the order (that belongs to the `converter` and its `strategies`).## User Stories & Use Cases**How will users interact with the solution?**- As a developer, I want to receive an `order_score` after conversion so I can decide if the result is acceptable.- As a conversion strategy developer, I want to see which chunks are misplaced to identify logic errors in my `reading_order` detector.- As a user, I want the validation report to fail if the text order is significantly broken (>2% displacement).## Success Criteria**How will we know when we're done?**- The system correctly identifies identical sequences as 100% order score.- The system correctly flags swapped paragraphs with a score < 100%.- **Definition of Pass:** A score >= 98% is considered a successful order validation (allowing for minor noise/shifts).- Performance: Must be able to process a 300-page book in seconds using chunk-based LCS.## Constraints & Assumptions**What limitations do we need to work within?**- **Assumption:** Both PDF and EPUB texts are already canonicalized and segmented into chunks.- **Constraint:** Must use the `text_segmenter` outputs to ensure consistency.## Questions & Open Items**What do we still need to clarify?**- What is the best mathematical approach for `order_score`? (LCS vs Kendall Tau distance). Product vision suggests LCS.

Frequently asked questions

905 Feature Order Checker 00999d80