LM Studio plugins add web image analysis for vision-capable LLMs
A developer has created plugins for LM Studio that allow vision-capable LLMs to fetch images from the web and analyze them directly within the application. The plugins work without requiring MCP/APIs or registration, using simple scripts that can be installed with one click from the LM Studio website.
Key Features
The main plugin, "analyze-images," enables LLMs to:
- Fetch images from the web for analysis
- Chain tools automatically based on the task
- Convert fetched images into smaller thumbnail files for chat embedding to avoid clutter
- Use full-resolution images for analysis when possible
- Embed images in responses or use markdown table galleries when users request multiple images
The developer also updated existing plugins:
- Duck-Duck-Go plugin now works with images
- Visit Website plugin now works with images
Requirements and Setup
To use these plugins, you need:
- A vision-capable model (Qwen 3.5 9b or 27b are recommended)
- LM Studio with plugin support
The developer shared specific Qwen 3.5 settings that worked well:
Temperature: 1 Top K sampling: 20 Repeat Penalty: 1 Presence Penalty: 1.9 Top P sampling: 0.95 Min P sampling: 0
They noted that the Presence Penalty setting at 1.9 helped fix repetition problems and prevent loops.
The system prompt used was: "You are a capable, thoughtful, and precise assistant. Always prioritize being truthful, nuanced, insightful, and efficient, tailoring your responses specifically to the user's needs and preferences. Research before answering the questions: use both reasoning and tool calls to synthesize a proper conclusion."
Plugin Links
- Analyze Images plugin: https://lmstudio.ai/vadimfedenko/analyze-images
- Duck-Duck-Go reworked: https://lmstudio.ai/vadimfedenko/duck-duck-go-reworked
- Visit Website reworked: https://lmstudio.ai/vadimfedenko/visit-website-reworked
The developer also shared a Jinja Prompt Template on Pastebin that helped fix tool call errors.
📖 Read the full source: r/LocalLLaMA
👀 See Also
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Tendr Skill: Deterministic CLI Operations for Agent Memory Management
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read-once: A Claude Code Hook That Prevents Redundant File Reads
A developer built a PreToolUse hook called read-once that tracks files Claude Code has already read in a session, blocking re-reads of unchanged files and using diffs for changed files. The tool saves thousands of tokens per session by preventing Claude from repeatedly reading the same file content.
Jake Benchmark v1: Local LLM Performance Testing for OpenClaw AI Agents
A developer tested 7 local LLMs as AI agents with OpenClaw using 22 practical tasks including email processing, meeting scheduling, and phishing detection. Results ranged from 59.4% for Qwen 27B to 1.6% for Nemotron 30B, with detailed conversation logs available.