Llm Box
C 68 completed
Other
cli / python · small
75
Files
11,324
LOC
1
Frameworks
5
Languages
Pipeline State
completedRun ID
#390474Phase
doneProgress
1%Started
Finished
2026-04-13 01:31:02LLM tokens
0Pipeline Metadata
Stage
SkippedDecision
skip_scaffold_dupNovelty
31.87Framework unique
—Isolation
—Last stage change
2026-04-16 18:15:42Deduplication group #47545
Member of a group with 1 similar repo(s) — canonical #99059 view group →
Top concepts (2)
Project DescriptionTesting
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AI Prompt
Create a command-line tool, similar to `ls`, `cat`, and `find`, that uses large language models to enhance standard terminal operations. I need commands like `llm-box ls` to list files and provide AI-generated descriptions, `llm-box cat` to explain file contents instead of just dumping them, and `llm-box find` for semantic and fuzzy searching across a codebase. The tool should support configuration for various LLM providers, including Ollama, OpenAI, and Anthropic, and ideally allow indexing files for fast semantic search.
python cli llm command-line ai terminal ollama openai search
Generated by gemma4:latest
Catalog Information
llm-box brings the power of large language models to your command line. Instead of just listing files, it describes what they do. Instead of dumping file contents, it explains them. Instead of searching by filename, it understands what you're looking for.
Description
llm-box brings the power of large language models to your command line. Instead of just listing files, it describes what they do. Instead of dumping file contents, it explains them. Instead of searching by filename, it understands what you're looking for.
Novelty
3/10Tags
python cli llm command-line ai terminal ollama openai search
Technologies
anthropic langchain openai pydantic
Claude Models
claude-opus-4-6
Quality Score
C
67.8/100
Structure
82
Code Quality
55
Documentation
65
Testing
65
Practices
67
Security
82
Dependencies
60
Strengths
- CI/CD pipeline configured (github_actions)
- Code linting configured (ruff (possible))
- Consistent naming conventions (snake_case)
- Good security practices \u2014 no major issues detected
- Properly licensed project
Weaknesses
- Potential hardcoded secrets in 1 files
- 1239 duplicate lines detected \u2014 consider DRY refactoring
- 2 'god files' with >500 LOC need decomposition
Recommendations
- Move hardcoded secrets to environment variables or a secrets manager
Security & Health
4.1h
Tech Debt (A)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (1)
Repobility (the analyzer behind this table) · https://repobility.com
MIT
License
12.3%
Duplication
Languages
Frameworks
pytest
Concepts (2)
| Category | Name | Description | Confidence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Generated by Repobility's multi-pass static-analysis pipeline (https://repobility.com) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_description | Project Description | <strong>LLM-powered terminal toolbox</strong> — AI-enhanced versions of <code>ls</code>, <code>cat</code>, <code>find</code>, and more. | 80% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_category | Testing | testing | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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