File Operations Skill for Claude
Analyze files and get detailed metadata including size, line counts, modification times, and content statistics. Use when users request file information, statistics, or analysis without modifying files.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/mhattingpete/claude-skills-marketplace --skill file-operationsThe instruction itself
15 sections, as written by the authorFile Operations
Analyze files and retrieve metadata using Claude's native tools without modifying files.
When to Use
- "analyze [file]"
- "get file info for [file]"
- "how many lines in [file]"
- "compare [file1] and [file2]"
- "file statistics"
Core Operations
File Size & Metadata
stat -f "%z bytes, modified %Sm" [file_path] # Single file
ls -lh [directory] # Multiple files
du -h [file_path] # Human-readable size
Line Counts
wc -l [file_path] # Single file
wc -l [file1] [file2] # Multiple files
find [dir] -name "*.py" | xargs wc -l # Directory total
Content Analysis
Use Read to analyze structure, then count functions/classes/imports.
Pattern Search
Grep(pattern="^def ", output_mode="count", path="src/") # Count functions
Grep(pattern="TODO|FIXME", output_mode="content", -n=true) # Find TODOs
Grep(pattern="^import ", output_mode="count") # Count imports
Find Files
Glob(pattern="**/*.py")
Workflow Examples
Comprehensive File Analysis
- Get size/mod time:
stat -f "%z bytes, modified %Sm" file.py - Count lines:
wc -l file.py - Read file:
Read(file_path="file.py") - Count functions:
Grep(pattern="^def ", output_mode="count") - Count classes:
Grep(pattern="^class ", output_mode="count")
Compare File Sizes
- Find files:
Glob(pattern="src/**/*.py") - Get sizes:
ls -lh src/**/*.py - Total size:
du -sh src/*.py
Code Quality Metrics
- Total lines:
find . -name "*.py" | xargs wc -l - Test files:
find . -name "test_*.py" | wc -l - TODOs:
Grep(pattern="TODO|FIXME|HACK", output_mode="count")
Find Largest Files
find . -type f -not -path "./node_modules/*" -exec du -h {} + | sort -rh | head -20
Best Practices
- Non-destructive: Use Read/stat/wc, never modify
- Efficient: Read small files fully, use Grep for large files
- Context-aware: Compare to project averages, suggest optimizations
Integration
Works with:
- code-auditor: Comprehensive analysis
- code-transfer: After identifying large files
- codebase-documenter: Understanding file purposes
Other skills for the same job
different authors, same section of the catalogue
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.
Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.
Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
How to use it
Take mhattingpete/file-operations from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.