Does it require a specific model to run the analysis?

Yes, it typically dispatches a sub-agent using the Haiku model to perform the computational parsing and script execution for the comparison report.

Does this skill work with any git branch?

No, this skill is specifically designed to operate on branches with the 'autonomy/' prefix that follow the autonomy plugin's structured commit conventions.

What happens if my branches have no common ancestor?

The skill requires a common ancestor (git merge-base) to identify where the logic diverged. If none exists, it will return an error explaining that the histories are independent.

Will this skill merge my branches together?

No, it is a read-only comparison tool. It analyzes differences to provide insights and recommendations but does not perform any git merge or checkout operations.

How are metrics compared between branches?

The skill dispatches a branch-analyzer agent that parses metadata from your journaled commit messages and executes a Python script to calculate quantitative trajectories.

Comparing Branches

Name: Comparing Branches
Author: tilmon-engineering

bytilmon-engineering

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开发者工具

Compares two autonomy branches to evaluate divergent technical approaches, metrics, and experimental outcomes.

关于

The Comparing Branches skill is designed for developers using the autonomy workflow to objectively assess the differences between two experimental paths. By automatically identifying the git divergence point and dispatching a specialized branch-analyzer sub-agent, it performs a computational analysis of commit history, iteration progress, and tracked metrics like revenue or build performance. This skill eliminates subjective 'eyeballing' of code, providing a data-driven markdown report that highlights key achievements, blockers, and cross-branch learning opportunities to inform strategic project decisions.

主要功能

Insight generation for cross-branch learning and strategy selection
Automated divergence point detection using git merge-base
2 GitHub stars
Read-only history analysis that preserves branch integrity
Detailed iteration tracking across parallel experimental branches
Computational comparison of metrics using Python-based analysis

使用场景

Comparing the revenue impact and implementation complexity of different pricing models
Evaluating two different architectural approaches to solve the same performance bottleneck
Analyzing parallel feature experiments to determine which path provides better outcome metrics

关于

主要功能

Insight generation for cross-branch learning and strategy selection
Automated divergence point detection using git merge-base
2 GitHub stars
Read-only history analysis that preserves branch integrity
Detailed iteration tracking across parallel experimental branches
Computational comparison of metrics using Python-based analysis

使用场景

Comparing the revenue impact and implementation complexity of different pricing models
Evaluating two different architectural approaches to solve the same performance bottleneck
Analyzing parallel feature experiments to determine which path provides better outcome metrics