Can this skill handle complex logical constraints?

Yes, it specifically extracts conditionals, temporal dependencies, and exclusion constraints to map how information relates structurally within the document.

Why are the document extractions performed in parallel?

Parallel execution prevents the analysis of the second document from being biased by the first, ensuring independent discovery and reducing total processing time by 50%.

How does this differ from a standard text diff tool?

Standard diff tools find character or word changes; this skill identifies changes in meaning and logical flow, even if the wording or organization is completely different.

Is the comparison result deterministic?

While the skill uses temperature=0 and pinned models to maximize reproducibility, a 1-2% variance is expected due to the inherent nature of LLM semantic judgment.

What is an 'execution equivalence score'?

It is a weighted metric combining claim similarity (40%), relationship preservation (40%), and graph topology (20%) to measure how similar the documents are functionally.

Semantic Document Comparison

Name: Semantic Document Comparison
Author: cowwoc

bycowwoc

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学習とドキュメンテーション

Compares two documents semantically using claim extraction and relationship mapping to identify structural and content differences beyond simple text changes.

The compare-docs skill provides a sophisticated methodology for analyzing changes between documents by focusing on semantic meaning rather than line-by-line text diffs. By independently extracting atomic claims and mapping complex inter-relationships—such as temporal dependencies, conditional logic, and prerequisites—in a parallel workflow, it calculates a comprehensive execution equivalence score. This ensures that users can identify not just what words changed, but whether the underlying logic, constraints, or procedural requirements of a document have been preserved or compromised.

主な機能

01Parallel extraction of semantic claims to ensure unbiased, independent discovery

02Deep relationship mapping for temporal, conditional, and exclusion constraints

03Automated normalization of tense, voice, and synonyms for consistent analysis

04Detailed reporting of shared versus unique claims and preserved logical graphs

0556 GitHub stars

06Execution equivalence scoring based on claim, relationship, and graph similarity

ユースケース

01Auditing versions of policy documents to identify subtle shifts in logic or compliance constraints

02Comparing procedural guides to ensure step-by-step dependencies remain intact across iterations

03Verifying that a rewritten technical specification preserves all original functional requirements

主な機能

01Parallel extraction of semantic claims to ensure unbiased, independent discovery

02Deep relationship mapping for temporal, conditional, and exclusion constraints

03Automated normalization of tense, voice, and synonyms for consistent analysis

04Detailed reporting of shared versus unique claims and preserved logical graphs

0556 GitHub stars

06Execution equivalence scoring based on claim, relationship, and graph similarity

ユースケース

01Auditing versions of policy documents to identify subtle shifts in logic or compliance constraints

02Comparing procedural guides to ensure step-by-step dependencies remain intact across iterations

03Verifying that a rewritten technical specification preserves all original functional requirements