Analyze Results

Analyze Results is a Data skill for Claude Code, published by wanshuiyin in Auto-claude-code-research-in-sleep.

14.7K stars1.3K forkson wanshuiyin/Auto-claude-code-research-in-sleepAdded 2026/08/14Repository updated 2026/08/11

ai-researchai-toolsarisautonomous-agentclaudeclaude-codeclaude-code-skillscodexdeep-learninggptidea-generationllmmachine-learningmcpmcp-serverml-researchopenaipaper-reviewpaper-writingresearch-automation

Install in seconds

Install Analyze Results

Copy Analyze Results into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/analyze-results ~/.claude/skills/analyze-results

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/analyze-results/SKILL.md in wanshuiyin/Auto-claude-code-research-in-sleep
Installs to: ~/.claude/skills/analyze-results
Collection: One of 25 skills cataloged from this repository
Category: Data — 668 skills

What Analyze Results does

Analyze Results analyzes ML experiment results, computes statistics, and generates comparison tables and insights. Use when the user says "analyze results", "compare", or needs to interpret experimental data.

Analyze Results is cataloged under Data on DirSkills. Analyze Results comes from a repository tagged ai-research, ai-tools, aris, autonomous-agent and claude.

Documentation

README

Excerpt

Check figures/, results/, or project-specific output directories
Parse JSON results into structured data

Step 2: Build Comparison Table

Organize results by:

Independent variables: model type, hyperparameters, data config
Dependent variables: primary metric (e.g., perplexity, accuracy, loss), secondary metrics
Delta vs baseline: always compute relative improvement

Step 3: Statistical Analysis

If multiple seeds: report mean +/- std, check reproducibility
If sweeping a parameter: identify trends (monotonic, U-shaped, plateau)
Flag outliers or suspicious results

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Analyze Results

What else does wanshuiyin publish alongside Analyze Results?
Analyze Results is one of 25 skills that DirSkills catalogs from wanshuiyin/Auto-claude-code-research-in-sleep, the repository it ships in. Its siblings there include Ablation Planner, AlphaXiv and ArXiv Paper Search. Each one is a separate skill with its own page in this directory, installs the same way Analyze Results does, and is maintained by wanshuiyin in that same repository. The rest of the collection is listed on the wanshuiyin/Auto-claude-code-research-in-sleep page.
How does Analyze Results compare to other Data skills?
Analyze Results ranks #120 by stars among the 668 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Analyze Results against them. Open each page to compare what they document and how they install.