LLM CLI Skill

Purpose

llm

When to Use This Skill

• User wants to process text/files with an LLM
• User needs to choose between multiple available LLMs
• User wants interactive conversation with an LLM
• User needs to pipe content through an LLM for processing
• User wants to use specific model aliases (e.g., "claude-opus", "gpt-4o")

• "Process this file with Claude"
• "Analyze this text with the fastest available model"
• "Start an interactive chat with OpenAI"
• "Use Gemini to summarize this document"
• "Chat mode with my local Ollama instance"

Supported Providers & Models

OpenAI

• Latest Models (2025):

  • gpt-5

    - Most advanced model

  • gpt-4-1

    /

    gpt-4.1

    - Latest high-performance

  • gpt-4-1-mini

    /

    gpt-4.1-mini

    - Smaller, faster version

  • gpt-4o

    - Multimodal omni model

  • gpt-4o-mini

    - Lightweight multimodal

  • o3

    - Advanced reasoning

  • o3-mini

    /

    o3-mini-high

    - Reasoning variants

openai

gpt

Anthropic

• Latest Models (2025):

  • claude-sonnet-4.5

    - Latest flagship model

  • claude-opus-4.1

    - Complex task specialist

  • claude-opus-4

    - Coding specialist

  • claude-sonnet-4

    - Balanced performance

  • claude-3.5-sonnet

    - Previous generation

  • claude-3.5-haiku

    - Fast & efficient

anthropic

claude

Google Gemini

• Latest Models (2025):

  • gemini-2.5-pro

    - Most advanced

  • gemini-2.5-flash

    - Default fast model

  • gemini-2.5-flash-lite

    - Speed optimized

  • gemini-2.0-flash

    - Previous generation

  • gemini-2.5-computer-use

    - UI interaction

google

gemini

Ollama (Local)

• Popular Models:

  • llama3.1

    - Meta's latest (8b, 70b, 405b)

  • llama3.2

    - Compact versions (1b, 3b)

  • mistral-large-2

    - Mistral flagship

  • deepseek-coder

    - Code specialist

  • starcode2

    - Code models

ollama

local

Workflow Overview

User Input (with optional model)
    ↓
Check Available Providers (env vars)
    ↓
Determine Model to Use:
  - If specified: Use provided model
  - If ambiguous: Show selection menu
  - Otherwise: Use last remembered choice
    ↓
Load/Create Config (~/.claude/llm-skill-config.json)
    ↓
Detect Input Type:
  - stdin/piped
  - file path
  - inline text
    ↓
Execute llm CLI:
  - Non-interactive: Process & return
  - Interactive: Keep conversation loop
    ↓
Save Model Choice to Config

Features

1. Provider Detection

• Checks environment variables for API keys
• Suggests available LLM providers on first run
• Detects:

  OPENAI_API_KEY

  ,

  ANTHROPIC_API_KEY

  ,

  GOOGLE_API_KEY

  ,

  OLLAMA_BASE_URL

2. Model Selection

• Accept model aliases (

  gpt-4o

  ,

  claude-opus

  ,

  gemini-2.5-pro

  )
• Accept provider aliases (

  openai

  ,

  anthropic

  ,

  google

  ,

  ollama

  )
• Interactive menu when selection is ambiguous
• Remembers last used model in

  ~/.claude/llm-skill-config.json

3. Input Processing

• Accepts stdin/piped input
• Processes file paths (detects: .txt, .md, .json, .pdf, images)
• Handles inline text prompts
• Supports multimedia files with appropriate encoding

4. Execution Modes

Non-Interactive (Default)

llm "Your prompt here"
llm --model gpt-4o "Process this text"
llm < file.txt
cat document.md | llm "Summarize"

Interactive Mode

llm --interactive
llm -i
llm --model claude-opus --interactive

5. Configuration

~/.claude/llm-skill-config.json

{
  "last_model": "claude-sonnet-4.5",
  "default_provider": "anthropic",
  "available_providers": ["openai", "anthropic", "google", "ollama"]
}

Implementation Details

Core Files

• llm_skill.py

  - Main skill orchestration

• providers.py

  - Provider detection & config

• models.py

  - Model definitions & aliases

• executor.py

  - Execution logic (interactive/non-interactive)

• input_handler.py

  - Input type detection

Key Functions

detect_providers()

• Scans environment for provider API keys
• Returns dict of available providers

get_model_selector(input_text, provider=None)

• Returns selected model, showing menu if needed
• Respects

  last_model

  config preference

load_input(input_source)

• Handles stdin, file paths, or inline text
• Returns content string

execute_llm(content, model, interactive=False)

• Calls

  llm

  CLI with appropriate parameters
• Manages stdin/stdout for interactive mode

Usage in Claude Code

1. Parse input for model specification (e.g.,

   --model gpt-4o

   )
2. Call skill with content and optional model parameter
3. Wait for provider/model selection if needed
4. Execute and return results
5. For interactive mode, maintain conversation loop

Error Handling

• If no providers available: Suggest installing API keys
• If model not found: Show available models for chosen provider
• If llm CLI not installed: Suggest installation via

  pip install llm

• If file not readable: Fall back to treating as inline text

Configuration

{
  "last_model": "claude-sonnet-4.5",
  "default_provider": "anthropic",
  "interactive_mode": false,
  "available_providers": ["openai", "anthropic"]
}

Slash Command Integration

/llm

/llm process this text
/llm --interactive
/llm --model gpt-4o analyze this