How does the skill decide if a resource is worth storing?

It uses an Importance Criteria rubric that weighs novelty (25%), applicability (30%), durability (20%), connectivity (15%), and authority (10%) to generate a priority score.

What is the 'Tidying Imperative' feature?

It is a cleanup process inspired by the KonMari method that helps you identify and archive knowledge that is no longer aligned with your current project goals or professional aspirations.

Can this skill update my code automatically based on an article?

Yes, through Application Routing, it can identify bug fix patterns or performance optimizations and suggest direct updates to your local codebase or documentation.

What happens if I provide a resource that already exists in my documentation?

The Marginal Value Filter performs a redundancy check. If the overlap is too high without providing new insights, it will suggest skipping or merging the content rather than creating a duplicate entry.

Knowledge Intake for Memory Palace

Name: Knowledge Intake for Memory Palace
Author: athola

byathola

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Learning & Documentation

Transforms external resources like articles and papers into structured, actionable knowledge with systematic evaluation and application routing.

About

Knowledge Intake acts as a sophisticated governance framework for your digital knowledge base, ensuring every external resource shared with Claude is vetted for relevance and novelty. It uses a multi-weighted evaluation rubric to score content, determines whether insights apply to your local project or broader infrastructure, and employs a Marginal Value Filter to prevent redundant information from polluting your corpus. By integrating a KonMari-inspired tidying philosophy, it proactively prunes outdated data, maintaining a high-signal environment for long-term development and learning.

Key Features

Automatic URL and web content detection via built-in hooks
Automated application routing to codebase docs or meta-infrastructure skills
Multi-weighted evaluation framework scoring novelty, applicability, and durability
Marginal Value Filter to prevent redundant data and calculate teaching deltas
KonMari-inspired pruning workflows to archive outdated or unaligned knowledge
10 GitHub stars

Use Cases

Filtering high-noise technical documentation to extract specific implementation strategies
Building and maintaining a high-quality 'digital garden' of development patterns
Converting technical blog posts and research papers into actionable Architectural Decision Records

About

Key Features

Automatic URL and web content detection via built-in hooks
Automated application routing to codebase docs or meta-infrastructure skills
Multi-weighted evaluation framework scoring novelty, applicability, and durability
Marginal Value Filter to prevent redundant data and calculate teaching deltas
KonMari-inspired pruning workflows to archive outdated or unaligned knowledge
10 GitHub stars

Use Cases

Filtering high-noise technical documentation to extract specific implementation strategies
Building and maintaining a high-quality 'digital garden' of development patterns
Converting technical blog posts and research papers into actionable Architectural Decision Records