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Desktop analysis and reporting tools. An agent skill from MassLab-SII/open-agent-skills.
Install Desktop Analysis
$ npx skills add MassLab-SII/open-agent-skills --skill desktop-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install MassLab-SII/open-agent-skills desktop-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/MassLab-SII/open-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/portable-skills/desktop_analysis .claude/skills/desktop-analysis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "desktop-analysis" agent skill from https://github.com/MassLab-SII/open-agent-skills/tree/main/portable-skills/desktop_analysis into .claude/skills/desktop-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "desktop-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/MassLab-SII/open-agent-skills/tree/main/portable-skills/desktop_analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add MassLab-SII/open-agent-skills --skill desktop-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install MassLab-SII/open-agent-skills desktop-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MassLab-SII/open-agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/portable-skills/desktop_analysis .agents/skills/desktop-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "desktop-analysis" agent skill from https://github.com/MassLab-SII/open-agent-skills/tree/main/portable-skills/desktop_analysis into .agents/skills/desktop-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "desktop-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add MassLab-SII/open-agent-skills --skill desktop-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install MassLab-SII/open-agent-skills desktop-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MassLab-SII/open-agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/portable-skills/desktop_analysis .cursor/skills/desktop-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "desktop-analysis" agent skill from https://github.com/MassLab-SII/open-agent-skills/tree/main/portable-skills/desktop_analysis into .cursor/skills/desktop-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "desktop-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/MassLab-SII/open-agent-skills.git --path portable-skills/desktop_analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add MassLab-SII/open-agent-skills --skill desktop-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install MassLab-SII/open-agent-skills desktop-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MassLab-SII/open-agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/portable-skills/desktop_analysis .gemini/skills/desktop-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "desktop-analysis" agent skill from https://github.com/MassLab-SII/open-agent-skills/tree/main/portable-skills/desktop_analysis into .gemini/skills/desktop-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "desktop-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install MassLab-SII/open-agent-skills desktop-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add MassLab-SII/open-agent-skills --skill desktop-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/MassLab-SII/open-agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/portable-skills/desktop_analysis .github/skills/desktop-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "desktop-analysis" agent skill from https://github.com/MassLab-SII/open-agent-skills/tree/main/portable-skills/desktop_analysis into .github/skills/desktop-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "desktop-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add MassLab-SII/open-agent-skills --skill desktop-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install MassLab-SII/open-agent-skills desktop-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MassLab-SII/open-agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/portable-skills/desktop_analysis .opencode/skills/desktop-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "desktop-analysis" agent skill from https://github.com/MassLab-SII/open-agent-skills/tree/main/portable-skills/desktop_analysis into .opencode/skills/desktop-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "desktop-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
desktop-analysis- GitHub stars
- 133
- Token cost
- ~1.6k tokens
- SKILL.md length
- 527 words
- Files
- 5 (incl. scripts)
- Skills in repo
- 7
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Desktop analysis and reporting tools. An agent skill from MassLab-SII/open-agent-skills.
- Works in 3 steps: Music Analysis Report → File Statistics → List All Files
- Tasks that involve Statistics
- SKILL.md covers Important Notes, I. Skills and II. Basic Tools…
- Runs Python scripts from its folder; calls python
What it does
Desktop Analysis is an agent skill from MassLab-SII/open-agent-skills. Desktop analysis and reporting tools. Includes music analysis with popularity scoring and file statistics (count files, folders, and calculate total size).
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts (for example `scripts/file_statistics.py`, `scripts/list_all_files.py` and `scripts/music_report.py`).
It sits in Data & Analytics, covering Statistics. The repository describes itself as: We are dedicated to building a set of open agent skills that deliver superior performance, higher determinism, and greater consistency on targeted tasks, while operating at a… The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Statistics
Example prompts
- “/desktop-analysis”
Requirements
- Python 3
Workflow steps
3 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit ece5fab. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 4 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Desktop Analysis loads about 1.6k tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 527 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from MassLab-SII/open-agent-skills at commit ece5fab, republished under its Apache-2.0 licence (© MassLab-SII). 527 words, ~1,610 tokens.
Download SKILL.mdSave it as
.claude/skills/desktop-analysis/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- desktop-analysis
- description
- Desktop analysis and reporting tools. Includes music analysis with popularity scoring and file statistics (count files, folders, and calculate total size).
Desktop Analysis Skill
This skill provides data analysis and reporting tools:
- Music analysis: Generate popularity reports from music data
- File statistics: Count files, folders, and calculate total size
- List all files: Recursively list all files under a directory
Important Notes
- Do not use other bash commands: Do not attempt to use general bash commands or shell operations like cat, ls.
- Use relative paths: Use paths relative to the working directory (e.g.,
./folder/file.txtorfolder/file.txt).
I. Skills
1. Music Analysis Report
Analyzes music data from multiple artists, calculates popularity scores using a weighted formula, and generates a detailed analysis report.
Features
- Reads song data from multiple artist directories
- Supports CSV and TXT file formats
- Calculates popularity scores using configurable weights:
popularity_score = (rating × W1) + (play_count_normalized × W2) + (year_factor × W3)- Default weights: W1=0.4, W2=0.4, W3=0.2
- Sorts songs by popularity
Parameters
| Parameter | Default | Description |
|---|---|---|
--output | music_analysis_report.txt | Output report filename |
--rating-weight | 0.4 | Weight for rating score |
--play-count-weight | 0.4 | Weight for normalized play count |
--year-weight | 0.2 | Weight for year factor |
Example
# Generate music analysis report with default weights (0.4, 0.4, 0.2)
python music_report.py ./music
# Use a custom output filename
python music_report.py ./music --output my_report.txt
# Use custom weights for the popularity formula
python music_report.py ./music --rating-weight 0.5 --play-count-weight 0.3 --year-weight 0.22. File Statistics
Generate file statistics for a directory: total files, folders, and size.
Features
- Count total files (excluding .DS_Store)
- Count total folders
- Calculate total size in bytes (includes .DS_Store for size only)
Example
python file_statistics.py .3. List All Files
Recursively list all files under a given directory path. Useful for quickly understanding project directory structure.
Features
- Recursively traverse all subdirectories
- Option to exclude hidden files (like .DS_Store)
- Output one file path per line, including both path and filename (relative to input directory)
Example
# List all files (excluding hidden)
python list_all_files.py .
# Include hidden files
python list_all_files.py ./data --include-hiddenII. Basic Tools (FileSystemTools)
Below are the basic tool functions. These are atomic operations for flexible combination.
Prefer Skills over Basic Tools: When a task matches one of the Skills above, use the corresponding Skill instead of Basic Tools. Skills are more efficient because they can perform batch operations in a single call.
Prefer List All Files over list_directory/list_files: When you need to list files in a directory, prefer using the list_all_files.py skill instead of list_directory or list_files basic tools. The skill provides recursive listing with better output formatting.
Note: Code should be written without line breaks.
Show full SKILL.md (181 more words)Show less
How to Run
# Standard format
python run_fs_ops.py -c "await fs.read_text_file('./file.txt')"File Reading Tools
read_text_file(path, head=None, tail=None)
Use Cases:
- Read complete file contents
- Read first N lines (head) or last N lines (tail)
Example:
python run_fs_ops.py -c "await fs.read_text_file('./data/file.txt')"read_multiple_files(paths)
Use Cases:
- Read multiple files simultaneously
Example:
python run_fs_ops.py -c "await fs.read_multiple_files(['./a.txt', './b.txt'])"File Writing Tools
write_file(path, content)
Use Cases:
- Create new files with short, simple content only
- Overwrite existing files
⚠️ Warning: Do NOT include triple backticks (```) in the content, as this will break command parsing.
Example:
python run_fs_ops.py -c "await fs.write_file('./new.txt', 'Hello World')"edit_file(path, edits)
Use Cases:
- Make line-based edits to existing files
Example:
python run_fs_ops.py -c "await fs.edit_file('./file.txt', [{'oldText': 'foo', 'newText': 'bar'}])"Directory Tools
create_directory(path)
Use Cases:
- Create new directories (supports recursive creation)
Example:
python run_fs_ops.py -c "await fs.create_directory('./new/nested/dir')"list_directory(path)
Use Cases:
- List all files and directories in a path
Example:
python run_fs_ops.py -c "await fs.list_directory('.')"list_files(path=None, exclude_hidden=True)
Use Cases:
- List only files in a directory
Example:
python run_fs_ops.py -c "await fs.list_files('./data')"File Operations
move_file(source, destination)
Use Cases:
- Move or rename files/directories
Example:
python run_fs_ops.py -c "await fs.move_file('./old.txt', './new.txt')"search_files(pattern, base_path=None)
Use Cases:
- Search for files matching a glob pattern
Example:
python run_fs_ops.py -c "await fs.search_files('*.txt')"File Information
get_file_info(path)
Use Cases:
- Get detailed metadata (size, created, modified, etc.)
Example:
python run_fs_ops.py -c "await fs.get_file_info('./file.txt')"get_file_size(path)
Use Cases:
- Get file size in bytes
Example:
python run_fs_ops.py -c "await fs.get_file_size('./file.txt')"get_file_ctime(path) / get_file_mtime(path)
Use Cases:
- Get file creation/modification time
Example:
python run_fs_ops.py -c "await fs.get_file_mtime('./file.txt')"get_files_info_batch(filenames, base_path=None)
Use Cases:
- Get file information for multiple files in parallel
Example:
python run_fs_ops.py -c "await fs.get_files_info_batch(['a.txt', 'b.txt'], './data')"© MassLab-SII, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 4 other files (scripts) in portable-skills/desktop_analysis of MassLab-SII/open-agent-skills.
- SKILL.md
- scripts/file_statistics.py
- scripts/list_all_files.py
- scripts/music_report.py
- scripts/utils.py
Open the folder on GitHubat commit ece5fab
Compare with similar skills
Desktop Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Desktop Analysis this skillMassLab-SII/open-agent-skills | 133 | — | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Sandbox Benchvercel/next.js | 143k | — | ~4.1k | Automated safety check: Pass | MIT | |
| Statistical Analysisspacering-net/codeg | 3.9k | 3 repos | ~5k | Automated safety check: Pass | MIT | |
| StatsmodelszLanqing/codex-claude-academic-skills | 4.7k | 15 repos | ~4.9k | Automated safety check: Pass | BSD-3-Clause | |
| AI Daily DigestvigorX777/ai-daily-digest | 1.6k | — | ~1.3k | Automated safety check: Pass | None | |
| Statistical Powerspacering-net/codeg | 3.9k | 1 repos | ~3.6k | Automated safety check: Notes | MIT |
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- Official
Statistical Analysis
spacering-net/codeg
Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting.
Statsmodels
zLanqing/codex-claude-academic-skills
Statistical models library for Python. An agent skill from zLanqing/codex-claude-academic-skills.
AI Daily Digest
vigorX777/ai-daily-digest
Fetches RSS feeds from 90 top Hacker News blogs (curated by Karpathy), uses AI to score and filter articles, and generates a daily digest in Markdown with Chinese-translated titles, category…
Statistical Power
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Sample-size and statistical power calculations for planning studies.
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Related
Categories
Questions about Desktop Analysis
What does Desktop Analysis do?
Desktop analysis and reporting tools. An agent skill from MassLab-SII/open-agent-skills. Desktop Analysis is an agent skill from MassLab-SII/open-agent-skills. Desktop analysis and reporting tools.
When should I use Desktop Analysis?
Desktop Analysis fits situations like: tasks that involve Statistics.
How do I install Desktop Analysis in Claude Code?
Run `npx skills add MassLab-SII/open-agent-skills --skill desktop-analysis -a claude-code`. Or copy the skill folder (portable-skills/desktop_analysis in MassLab-SII/open-agent-skills) into .claude/skills/desktop-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Desktop Analysis in Codex?
Run `npx skills add MassLab-SII/open-agent-skills --skill desktop-analysis -a codex`. Or copy the skill folder (portable-skills/desktop_analysis in MassLab-SII/open-agent-skills) into .agents/skills/desktop-analysis in your project. Codex loads it when a task matches its description.
Can I use Desktop Analysis in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add MassLab-SII/open-agent-skills --skill desktop-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/desktop-analysis, .gemini/skills/desktop-analysis, .github/skills/desktop-analysis and .opencode/skills/desktop-analysis in your project.
What does Desktop Analysis need to run?
Going by SKILL.md and its folder, Desktop Analysis needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Desktop Analysis access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Desktop Analysis safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Desktop Analysis use?
Desktop Analysis is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Desktop Analysis use?
About 1.6k tokens (SKILL.md is roughly 6.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Desktop Analysis?
Skills that share tags, products or a category with Desktop Analysis: Sandbox Bench (vercel/next.js, 143k stars), Statistical Analysis (spacering-net/codeg, 3.9k stars), Statsmodels (zLanqing/codex-claude-academic-skills, 4.7k stars) and AI Daily Digest (vigorX777/ai-daily-digest, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Desktop Analysis?
MassLab-SII (a GitHub organization) maintains it in MassLab-SII/open-agent-skills, which has 133 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on December 29, 2025.
Source: MassLab-SII/open-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.