What sources does the skill use to find project history?

The skill searches through Architecture Decision Records (ADRs), git commit logs, pull request discussions, and internal documentation folders like /docs/decisions.

What is knowledge lineage tracing?

Knowledge lineage tracing is the practice of investigating the history and evolution of technical decisions to understand why a system is built a certain way before making changes.

Can it help me evaluate new frameworks or libraries?

Yes, it helps you map the 'new' approach against similar historical patterns (like SOAP vs GraphQL) to see what lessons can be applied from the past.

How does this skill help with technical debt?

It helps determine if legacy code was a 'hack' or a deliberate choice based on constraints that might still exist, preventing risky refactors that could re-introduce old bugs.

Knowledge Lineage Tracer

Name: Knowledge Lineage Tracer
Author: lifangda

bylifangda

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학습 및 문서화

Analyzes codebase history and decision records to understand architectural evolution and prevent repeating past failures.

소개

The Knowledge Lineage Tracer is a specialized skill for Claude Code designed to perform deep architectural archaeology within software projects. It helps developers understand the 'why' behind existing codebases by tracing the history of technical decisions, analyzing failed past attempts, and identifying when 'new' ideas are actually revivals of previous patterns. By systematically searching through Architecture Decision Records (ADRs), git logs, and documentation history, this skill ensures that modern development is informed by institutional memory, preventing the abandonment of proven solutions or the recurrence of historical mistakes.

주요 기능

Failed Attempt Analysis: Investigates why previous approaches were abandoned to see if current context makes them viable.
Revival Detection: Identifies historical precedents for 'new' ideas to avoid rebranding old solutions.
Paradigm Shift Mapping: Documents transitions between architectures to identify what capabilities were gained or lost.
Decision Archaeology: Scans ADRs and documentation to uncover the original logic behind current implementations.
16 GitHub stars
Automated Git History Search: Uses specialized git queries to find when specific patterns were introduced or removed.

사용 사례

Evaluating a proposal to replace an existing system by first understanding the constraints that led to its creation.
Investigating 'overcomplicated' code segments to discover non-obvious edge cases they were designed to solve.
Determining if a trending technology is a revival of a pattern the team has previously attempted and learned from.

소개

주요 기능

Failed Attempt Analysis: Investigates why previous approaches were abandoned to see if current context makes them viable.
Revival Detection: Identifies historical precedents for 'new' ideas to avoid rebranding old solutions.
Paradigm Shift Mapping: Documents transitions between architectures to identify what capabilities were gained or lost.
Decision Archaeology: Scans ADRs and documentation to uncover the original logic behind current implementations.
16 GitHub stars
Automated Git History Search: Uses specialized git queries to find when specific patterns were introduced or removed.

사용 사례

Evaluating a proposal to replace an existing system by first understanding the constraints that led to its creation.
Investigating 'overcomplicated' code segments to discover non-obvious edge cases they were designed to solve.
Determining if a trending technology is a revival of a pattern the team has previously attempted and learned from.