How to choose Anki HTML import settings without losing literal text

Label each relevant field by purpose. If a definition uses emphasis merely to help reading, the formatting is presentation. If a question asks what an HTML element means, the literal markup is the subject. If a mathematics prompt uses a less-than sign, that character carries meaning rather than decoration. A mixed sheet may contain all three. Write examples before deciding how the import should interpret them. The correct choice depends on the task, not the appearance of angle brackets alone.

The Anki text-import manual documents its HTML interpretation option and escaping rules. Read those mechanics alongside your actual fields. In the fictional computing sheet, the learner separates explanatory formatting from code examples in the planning map. They do not assume that a global choice can safely infer every row’s intent. If necessary, prepare a consistent representation of literal text before importing. Keep the original source untouched so a visual change can be compared with what the course actually asked the learner to recognize or produce.

Choose one field with intended emphasis, one literal tag, one comparison sign, and one ampersand if those occur in the real file. Include an ordinary text row to confirm that the basic map still works. Write the expected visible front and back for each. The sample tests meaning as well as rendering: the literal tag should remain a readable example, while intended formatting should not appear as distracting instructions unless that is what the task requires.

In the fictional course sheet, a row asks the learner to explain a displayed tag. Another uses bold text to distinguish an answer term from its explanation. A third asks about a condition involving a comparison symbol. Inspect each separately after import. A settings change that fixes the emphasis while breaking the code example is not a successful general repair. Preserve the sample and describe the tradeoff. That evidence tells you whether to separate the material, adjust escaping, or use a different content representation instead of repeatedly toggling a setting without a plan.

A useful sample worksheet has separate columns for raw field text and expected visible content. For the literal-code row, the expected content includes the brackets. For the emphasized-definition row, it includes the words with the intended presentation. This keeps the pass condition independent of the current renderer. Without that written expectation, it is easy to accept whichever result looks tidy even when the import has removed the subject of the question.

Use a plain-text view of the exported file to see the representation that will be interpreted. A rich editor may display the result and hide the markup itself. Compare the raw field with the expected card. Identify where literal characters need to remain literal and where formatting is intentional. Do not strip every bracketed fragment automatically. Some fragments are the exact content of the answer or question, particularly in computing and mathematical notation.

For a suspect row, copy the field into a small separate test file rather than editing the entire collection. Keep the source column map stable while changing only the representation under investigation. This isolates whether the issue is escaping, import interpretation, or the destination template. If the raw field is already missing a required symbol, the import option cannot reconstruct it. Regenerate or repair the source with a verified meaning first. The chain from source to file to preview to actual card should remain inspectable at every stage.

Formatting pasted from a webpage or document can carry more structure than the learner intended. A definition may include nested styles, links, or layout fragments that were useful on the original page but distracting on a small card. Inspect the actual exported representation and resulting question. The goal is not to preserve every visual detail; it is to preserve the information required to answer and verify the task. Remove unnecessary presentation only after identifying what it contributes.

In the fictional computing course, one pasted explanation has a large heading and an external link wrapped around the accepted answer. The learner chooses a simpler personal wording with a clear source reference. Another row contains literal code where the exact punctuation matters, so simplification must preserve those characters. These decisions differ because the role of the content differs. A single cleanup command that makes both rows look uniform could destroy the code example. Keep a small before-and-after comparison and explain each transformation in terms of the learning objective.

Do not paste unfamiliar scripts or template fragments merely because they were included in a shared study file. Inspect the material and use the documented import features appropriate to your task. A study definition rarely needs complex interactive markup just to ask a term and show an answer. If you cannot explain what a fragment does, remove it from the test copy or ask for a plain, authorized source rather than treating complexity as evidence of quality.

Check links and personal information separately from visual formatting. A shared field can contain a private document URL or an author’s note that should not be redistributed. Verify permission before moving the content to another workspace. This is a task-specific inspection, not a claim that every imported HTML field is unsafe. The practical principle is to understand and minimize what you carry forward. Preserve meaningful notation, keep source traceability, and avoid depending on opaque behavior when a straightforward question would serve the same learning goal.

Compare each representative card with the expected visible task. Can the learner read the literal symbols? Is the intended answer still hidden on the front? Does formatting make the question clearer rather than revealing the target? Inspect an actual review on the device you use, because a large desktop preview can conceal a mobile readability problem. Record unresolved cases instead of treating most rows looking normal as proof that the whole mixed sheet is correct.

For Elly, use a supported CSV, TSV, or TXT sample and inspect the receiving content independently. Anki HTML behavior is not a promise about another app’s rendering, and text import does not preserve native templates, media, scheduling, or review history. Keep the original collection while evaluating a permitted source-based task. If exact markup is the topic, verify every meaningful symbol in the receiving question. If the markup was only presentation, judge whether the simpler text still supports the intended explanation. The source and task determine acceptance, not cosmetic similarity alone.