AgentSkillsCN

Analyze Repo

深入分析相关 GitHub 仓库，将其架构与算法同 BreezeForest 进行对比

SKILL.md
--- frontmatter
description: Deep analysis of a related GitHub repository, comparing its architecture and algorithms with BreezeForest
allowed-tools: Bash, WebSearch, WebFetch, Read, Write, Glob, Grep, Task
argument-hint: <GitHub URL or local path, e.g. "https://github.com/nicola-decao/BNAF" or "./some-local-repo">

Analyze Repo

Perform a deep analysis of a repository related to normalizing flows / density estimation.

Target: $ARGUMENTS

Task: Comprehensive Repository Analysis

1. Access the Repository

Determine if $ARGUMENTS is a GitHub URL or local path:

If GitHub URL:

  • •Use gh repo clone [url] /tmp/analyze-repo-target -- --depth=1 to shallow clone
  • •Use gh api repos/{owner}/{repo} to get repo metadata (stars, forks, description, language)
  • •Set analysis path to the cloned directory

If local path:

  • •Verify the path exists
  • •Set analysis path to the provided path

2. Repository Overview

Gather basic information:

bash
# File structure
find [path] -type f -name "*.py" | head -50

# README
cat [path]/README.md

# Dependencies
cat [path]/requirements.txt or [path]/setup.py or [path]/pyproject.toml

# Git stats
git -C [path] log --oneline -20
git -C [path] shortlog -sn --no-merges | head -10

Record:

  • •Language/Framework: Python, PyTorch, TensorFlow, JAX, etc.
  • •Project maturity: Active development, stable, archived
  • •Contributors: Number and activity
  • •Documentation quality: README completeness, docstrings, examples

3. Architecture Analysis

Read the core source files to understand:

Model Architecture

  • •What type of normalizing flow is implemented? (autoregressive, coupling, continuous, residual)
  • •What are the building blocks? (layers, transforms, distributions)
  • •How is the model composed? (sequential, parallel, hierarchical)
  • •What base distributions are used?

Jacobian Computation

  • •How is the log-determinant of the Jacobian computed?
  • •Triangular structure exploited? LU decomposition? Trace estimation?
  • •Computational complexity

Training

  • •Loss function (negative log-likelihood, ELBO, other)
  • •Regularization techniques
  • •Optimization setup

Sampling / Inversion

  • •How are samples generated from the model?
  • •Analytical inverse? Iterative inversion? One-pass?

4. Code Quality Assessment

Evaluate:

  • •Code organization: Clean module structure? Separation of concerns?
  • •Extensibility: Easy to add new flow types or components?
  • •Testing: Test coverage and quality
  • •Documentation: Inline comments, docstrings, examples
  • •Reproducibility: Clear instructions to reproduce results

5. Comparison with BreezeForest

Compare against BreezeForest's key properties:

DimensionBreezeForest[Target Repo]
Flow typeAutoregressive (conditional CDF)?
ArchitectureTree + breeze connections?
JacobianNumerical diff / exact jacrev, O(N^2)?
UniversalityYes (1 hidden layer)?
SamplingBatched bisection?
Regularizationsap_w + MultiBF mixture?
Dimensions tested2D?

6. Identify Transferable Ideas

Look for techniques or patterns that could benefit BreezeForest:

  • •Better numerical methods
  • •Training tricks or schedules
  • •Architecture innovations
  • •Testing approaches
  • •Benchmark datasets and evaluation metrics
  • •Code organization patterns

7. Output Format

markdown
# Repository Analysis: [repo name]
**URL**: [GitHub URL]
**Date**: YYYY-MM-DD

## Overview
- **Description**: [what the project does]
- **Language**: [primary language/framework]
- **Stars**: [count] | **Forks**: [count]
- **Last active**: [date of last commit]
- **Maturity**: [active/stable/archived]

## Architecture

### Model Design
[Description of the model architecture with key insights]

### Key Components
- `[file]`: [what it does]
- `[file]`: [what it does]
- ...

### Jacobian Computation
[How log-det-Jacobian is computed, complexity]

### Training Pipeline
[Loss function, optimizer, regularization]

### Sampling
[How samples are generated]

## Code Quality
| Aspect | Rating | Notes |
|---|---|---|
| Organization | [Good/Fair/Poor] | [details] |
| Documentation | [Good/Fair/Poor] | [details] |
| Testing | [Good/Fair/Poor] | [details] |
| Reproducibility | [Good/Fair/Poor] | [details] |

## Comparison with BreezeForest
[Detailed comparison table and discussion]

### Similarities
- [similarity 1]
- [similarity 2]

### Differences
- [difference 1]
- [difference 2]

## Transferable Ideas
1. **[Idea]**: [description + how it could be applied to BreezeForest]
2. **[Idea]**: [description + how it could be applied to BreezeForest]
3. ...

## Summary
[2-3 paragraph summary of findings and recommendations]

## References
- [Paper or resource 1]
- [Paper or resource 2]

8. Save Results

Save to notes/repo_analysis/[repo_name]_YYYY_MM_DD.md. Create the directory if it doesn't exist.

9. Cleanup

If a temporary clone was created, remove it:

bash
rm -rf /tmp/analyze-repo-target