WebSnips Guides
How to search your library with WebSnips — a practical guide to WebSnips' search capabilities, including full-text search, filters, boolean operators, search within Collections, and how to find clips efficiently as your library grows.
When your library has 50 clips, you can browse through it. When it has 500, browsing stops working and search becomes essential. When it has 5,000, search quality determines whether your library is an asset or a pile.
A powerful search in a web clipping library needs to go beyond title and URL — it needs to search the full text of captured articles, the annotations you've written, the highlights you've marked, and the tags you've applied. It needs to support filters that let you narrow results by time, tag, Collection, and source type. And it needs to be fast enough that searching is faster than browsing would have been.
WebSnips search indexes the full content of every captured clip — not just the title and URL, but the complete article text, your annotation notes, your highlight text, and all applied tags. This guide covers how to use it effectively.
Accessing search:
/ from anywhere in the WebSnips application to focus the search barCmd+F / Ctrl+F as an alternative shortcutWhat gets searched:
When you type a search query, WebSnips searches:
This comprehensive indexing means you can search for a term that appeared in the article body (even if it's not in the title), a word you used in your own annotation, or a term from a highlight — and find the relevant clip.
Simple keyword search:
Type one or more keywords in the search bar. WebSnips returns clips where any of the indexed fields contain the keywords.
remote work productivity → clips containing all three terms somewhere in the clip
Phrase search:
Wrap a phrase in quotes to search for the exact phrase rather than individual words.
"deep work" → clips containing the exact phrase "deep work"
"attention economy" research → clips containing the phrase "attention economy" AND the word "research"
WebSnips supports search operators for more precise queries:
AND (default):
Multiple terms default to AND — both must be present.
remote work AND productivity = remote work productivity (same result)
OR:
Find clips that contain either term.
"attention economy" OR "information overload" → clips containing either phrase
NOT:
Exclude clips containing a term.
remote work NOT commuting → clips about remote work that don't mention commuting
Parentheses for grouping:
(remote OR distributed) AND (work OR team) → clips containing one of the first group AND one of the second group
For more precise searching, specify the field to search:
| Operator | Searches | Example |
|---|---|---|
title: | Only the clip title | title:productivity |
note: | Only your annotations | note:framework |
highlight: | Only highlighted passages | highlight:key finding |
tag: | Only tags | tag:case-study |
url: | The clip's source URL | url:harvard.edu |
author: | Extracted author metadata | author:Newport |
site: | The domain of the source | site:substack.com |
Examples:
tag:case-study AND site:hbr.org → Harvard Business Review articles you've saved and tagged as case studies
note:productivity highlight:flow state → clips where you mentioned "productivity" in your notes AND the text "flow state" appears in a highlight
title:knowledge management NOT tag:to-read → clips with "knowledge management" in the title that you haven't tagged as to-read
Filters apply constraints to search results without using search operators. Click Filter (funnel icon) next to the search bar to open the filter panel.
Available filters:
Date range:
Tags:
Collections:
Status:
Content type:
Source domain:
nytimes.com)Combining filters:
Filters are combinable. A query of:
machine learningresearch-paper, Date = last 6 monthsReturns only research papers about machine learning clipped in the last 6 months.
When a Collection is open in the sidebar, the search bar automatically scopes to that Collection.
To search only within a Collection:
To search across all Collections while a Collection is open:
Click the "All clips" toggle next to the search bar to expand the search back to the full library.
Searches you run frequently can be saved as Smart Collections — dynamic collections that always show clips matching a specific query.
Creating a Smart Collection from a search:
Example Smart Collections:
tag:to-read AND date:last-30-days → smart inbox of recently saved unread clipstag:case-study AND tag:product-management → all product management case studiesnote:important → all clips where you've written "important" in your annotationSmart Collections are "live" — they're always current without manual maintenance.
| Goal | Query example |
|---|---|
| Find exact phrase | "knowledge base" |
| Find either of two terms | Notion OR Obsidian |
| Exclude a term | productivity NOT Pomodoro |
| Search in title only | title:deep work |
| Search in your notes | note:evidence |
| Search in highlights | highlight:key claim |
| Search by tag | tag:case-study |
| Search by source domain | site:substack.com |
| Combine multiple conditions | tag:case-study AND note:evidence site:hbr.org |
| Recent clips on a topic | machine learning date:last-30-days |
Use field operators when you know where the term is:
If you remember writing something specific in your annotation notes, use note: to search only notes — it's faster and more precise than searching the full text of all captured articles.
Use phrase search for distinctive multi-word terms:
"Attention economy" is more distinctive than searching for "attention" and "economy" separately (which would match clips containing both words anywhere in the text). Phrase search is especially useful for named frameworks, people, and organization names.
Combine tags and text search:
If you've been consistent with tags, the combination of a tag filter and a text search is often more precise than a text-only search. tag:research-paper attention economy narrows to research papers you've saved about attention and the economy.
Use "site:" to find content from specific sources:
If you read primarily from a few trusted sources, site:stratechery.com distribution finds clips from Stratechery about distribution without searching your entire library.
Use date filters for time-bounded research:
When researching a current topic, [query] date:last-90-days limits to clips saved in the past 3 months — relevant for fast-moving topics where older clips may be outdated.
The clip exists but search doesn't surface it:
note:, highlight:, title:) if you remember which field the term is inThe capture may have been incomplete:
Some pages don't capture well (heavy JavaScript rendering, paywalled content). If a clip doesn't appear in search for a term you know is in the article, check the clip directly — the captured text may be incomplete. For important clips where full text wasn't captured, consider recapturing with "Full page" mode.
The library doesn't have the clip:
Use WebSnips Insights' "Unvisited" view to browse clips you haven't looked at recently — sometimes you're looking for a clip that exists but that you're looking for under the wrong search term.
Setup: A writer is drafting an article about the psychology of productivity. She knows she's clipped relevant material over the past year but can't remember the specific clips.
Her search session:
She presses / to open search and types deep work focus — returns 14 clips. She scans the titles; 5 are clearly relevant.
She searches "attention residue" — returns 3 clips including a specific academic paper she recalls seeing. She opens it.
She searches note:productivity evidence tag:research-paper — finds 8 research papers where she explicitly noted evidence in her annotations. 3 of these are new to her mental inventory.
She searches site:apa.org OR site:ncbi.nlm.nih.gov attention productivity — finds research from academic sources about attention and productivity. 4 results she wants to include.
She searches highlight:"cognitive load" — surfaces clips where she highlighted the phrase "cognitive load." Finds 2 clips she'd forgotten she highlighted.
Total search time: 12 minutes. She's found 22 relevant clips from a library of 800 without browsing.
title:, note:, tag:, site:) make searches more precise: when you know where the term is, field search is faster and more accurate than a general query."exact phrase") is more precise than multi-word searches: essential for distinctive terms like named frameworks, people, and organizations.tag:case-study AND note:evidence machine learning is far more targeted than any single-field search.WebSnips search is the mechanism that makes a large library useful: it transforms thousands of clips into an accessible knowledge base where any piece of captured content is findable in seconds. The basic search — type a query, get results — covers most use cases. Field-specific operators, boolean logic, and date filters extend that capability for precise retrieval. Smart Collections automate recurring searches so frequently-accessed query results are always one click away. The return on learning the search operators is high: users who search proficiently get more value from the same library than users who rely only on browsing and basic keyword search.
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