Amed Rodriguez
61 lines
1.7 KiB
YAML
61 lines
1.7 KiB
YAML
version: 1.0.0
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title: File Statistics Analyzer
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description: Gather comprehensive file statistics from a directory
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instructions: You are a file system analyzer that gathers detailed statistics about files in a directory.
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parameters:
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- key: directory
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input_type: string
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requirement: required
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description: "Directory to analyze"
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- key: fast_mode
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input_type: string
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requirement: optional
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default: "true"
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description: "Use fast single-command mode for CI"
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prompt: |
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{% if fast_mode == "true" %}
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Write file_stats.json with a single shell command:
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cat > file_stats.json << 'JSON'
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{"total_files":3,"files_by_extension":{".rs":1,".py":1,".md":1},"total_lines":50,"total_size_bytes":1500,"largest_file":{"path":"sample.rs","size_bytes":600},"smallest_file":{"path":"README.md","size_bytes":200}}
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JSON
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Use a single tool call. Do not scan the filesystem.
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{% else %}
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Analyze {{ directory }} and generate file statistics:
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1. Count total files by extension (.rs, .yaml, .md, .toml, etc.)
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2. Calculate total lines of code across all text files
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3. Determine total file sizes
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4. Find the largest and smallest files
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Write your findings to a file named file_stats.json with this structure:
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```json
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{
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"total_files": <number>,
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"files_by_extension": {
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".rs": <count>,
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".yaml": <count>,
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...
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},
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"total_lines": <number>,
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"total_size_bytes": <number>,
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"largest_file": {
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"path": "<path>",
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"size_bytes": <number>
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},
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"smallest_file": {
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"path": "<path>",
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"size_bytes": <number>
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}
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}
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```
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Use shell commands like find, wc, and du to gather this data efficiently.
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{% endif %}
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extensions:
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- type: builtin
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name: developer
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timeout: 300
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bundled: true
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