Interpreter

Updated 2026-04-09

LLM-backed feature inside Obsidian Web Clipper that analyzes, transforms, or compresses web content at capture time. Instead of only storing raw text, Interpreter can already generate summaries, translations, or structured extracts while clipping.

What Is New About It

Many capture workflows strictly separate collecting from thinking: save now, process later. Interpreter shifts part of that thinking into the moment of import. That is not automatically better, but it is often more efficient when you already know what form you will need later.

The decisive insight is that context matters more than the model alone. If you feed Interpreter the full HTML junk of a page, you get slower, more expensive, and often worse results. If you feed it a precise DOM slice, even smaller models can produce useful output.

Core Ideas

Prompt variables inside templates: prompts like {{"a summary of the page"}} turn the template into a lightweight transformation pipeline rather than just a storage template.

Context beats model size: in web clipping, poor input is often the real bottleneck.

One request, multiple outputs: the same clip can generate summary, translation, keywords, and structured notes in one pass.

Local models are realistic: runtimes like Ollama make private, local interpretation viable for sensitive notes.

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