Why use a git diff check in the workflow?

Using a git diff check allows the agent to only process changed files during routine syncs, significantly reducing execution time and token usage.

What is the Act-Learn-Reuse pattern?

It is a development workflow where an AI agent acts on a task, learns from the implementation by updating its expertise files, and reuses that updated knowledge for future tasks.

How does this skill prevent context bloat?

It includes strict MAX_LINES enforcement and priority-based summarization to keep expertise files concise, ensuring they stay within the AI's optimal context window.

Can it detect renamed or moved files?

Yes, the validation logic includes patterns to check for file existence and search for moved files by name to update paths in the expertise file automatically.

Self-Improve Prompt Designer

Name: Self-Improve Prompt Designer
Author: melodic-software

bymelodic-software

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Learning & Documentation

Automates the synchronization of AI expertise files with real-world codebase changes to prevent mental model drift.

About

This skill provides a comprehensive framework and template for building self-improving agent workflows within Claude Code. It implements the critical 'LEARN' phase of the Act-Learn-Reuse architectural pattern, ensuring that an AI's internal expertise files stay perfectly synced with the actual state of the codebase. By incorporating conditional git diff checks, strict line-limit enforcement, and automated validation logic, it allows developers to maintain high-quality, up-to-date documentation and mental models for AI agents without manual overhead or context bloat.

Key Features

Automated Expertise Syncing
Git Diff Optimization
Automated YAML Validation
Strict Line-Limit Enforcement
1 GitHub stars
Act-Learn-Reuse Workflow Integration

Use Cases

Preventing context window bloat by summarizing and prioritizing expertise content
Maintaining domain-specific expertise files for specialized agent roles
Automating the LEARN step in high-frequency development cycles

About

Key Features

Automated Expertise Syncing
Git Diff Optimization
Automated YAML Validation
Strict Line-Limit Enforcement
1 GitHub stars
Act-Learn-Reuse Workflow Integration

Use Cases

Preventing context window bloat by summarizing and prioritizing expertise content
Maintaining domain-specific expertise files for specialized agent roles
Automating the LEARN step in high-frequency development cycles