An Intelligent "Card Quality Assistant" to Help Users Avoid Common Pitfalls

Anki Suggestions
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Hello Anki developers and community members,

First, allow me to express my sincere gratitude for Anki. It’s a remarkable piece of software that has changed the way countless people learn.

I’m writing today to propose a feature that I believe could significantly help users (especially new ones) use Anki more effectively and build good card-creation habits from the very beginning.

The Problem:

At its core, Anki’s strength is its spaced repetition algorithm, which excels at answering the question of “when to review.” However, it is completely “agnostic” about “what to review”—the quality of the cards themselves. A well-known issue is “Garbage In, Garbage Out.” Users, particularly novices, can easily create cards that are too complex, contain too much information, or are ambiguous. This leads to frustration, a high rate of leeches, and ultimately, reduced learning efficiency, sometimes even causing users to abandon Anki.

The current solution relies on user self-reflection, reading extensive guides, or using third-party add-ons. But what if Anki itself could provide some basic, heuristic guidance?

My Proposal:

I propose building a “Card Quality Assistant” directly into Anki. This system would not need to understand the semantic content of the cards. Instead, it would proactively identify “potentially problematic cards” by analyzing metadata and user review patterns, then offer gentle suggestions to the user.

It could operate based on a few heuristics like these:

  1. Pre-Leech Warning: When a card has been lapsed 3-4 times in a short period (before hitting the official “leech” threshold), the system could prompt after a review: “You’ve forgotten this card several times. Have you considered breaking it down into simpler parts?”

  2. Complexity Warning: If a card’s front or back field contains a very large amount of text (e.g., >200 words), the system could display a small warning icon during card creation/editing. This would remind users to follow the “Minimum Information Principle.”

  3. Excessive Time Warning: If a user’s average time spent reviewing a specific card is significantly above their norm (e.g., >15 seconds), the system could flag it as a card that might need simplification.

  4. Over-Simplicity Warning: If a card is consistently and very quickly (e.g., under 1 second each time) answered as “Easy,” the system could suggest: “This card seems very easy for you. Would you like to consider suspending or deleting it?”

Implementation:

  • These warnings could be non-intrusive . For instance, a small :warning: icon could appear next to a flagged card in the Browser.

  • After reviewing a flagged card, a dismissible notification could appear at the bottom of the screen.

  • A “Card Health Report” tab could be added to the Stats page, summarizing all potentially problematic cards.

The Benefits:

  • Guides Good Habits: Proactively guides new users toward the golden rules of effective card creation.

  • Improves Learning Efficiency: Helps users identify and fix low-quality cards early, reducing frustration and wasted time.

  • Enhances User Experience: Makes Anki feel “smarter” and more “supportive,” rather than just a passive algorithm executor.

This is just an initial concept, and I’m sure the community and developers could devise an even more refined solution. I believe integrating this kind of intelligent feedback into Anki’s core would be a truly meaningful step forward in its evolution.

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  1. This just sounds like it would be annoying tbh.
  2. Different people study differently and you can’t say whether 200 words is too much (it can even be just there for reference; the user doesn’t read it each time).
  3. Some cards are just more time consuming than others, that’s the way it is and displaying a warning or having extra flags/icons isn’t going to help.
  4. Pressing easy takes less time and mental effort than reading a message then suspending the card.
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You’re right. For an experienced user who already has their own effective methods, a mandatory and unintelligent notification system would absolutely be annoying. I completely agree.

Perhaps I should clarify my core intention: this feature is primarily aimed at guiding new users to help them avoid common pitfalls when they are just starting out. For advanced users like yourself, it should be completely optional and highly customizable .

Regarding the points you raised, I’d like to elaborate on my thinking:

  1. On being “Annoying” and Intrusive: You are correct. Ideally, this feature should work silently in the background. It should never interrupt the review flow with pop-ups. A better approach might be to add a subtle flag in the Browser next to certain cards, or to generate an optional “Card Health Report” in the Stats screen. This way, the user would only see these suggestions when they actively decide to optimize their cards.

  2. On the “200 words is too much” rule: This is a perfect example of why rigid, hard-coded rules don’t work. The “reference material” scenario you mentioned is very common. A more refined system should allow users to customize the thresholds (e.g., you could set the word count limit to 9999 to disable it), or even specify which fields (like an “Extra” field) should be ignored by the word count. The key is to provide guidance , not impose restrictions .

  3. On “Time-Consuming” and “Too Easy” cards: I agree that a simple warning icon by itself isn’t very helpful. Its purpose, however, is to trigger a moment of self-reflection for the user. A novice might ask, “Why did this card take me so long? Oh, it’s because I crammed three concepts into one.” For the “too easy” cards, you’re spot on—the interaction cost of an immediate prompt is too high. A better solution might be to list these cards in bulk within the “Health Report,” allowing the user to process them all at once, which would be far more efficient.

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We currently have data from multiple sources to analyze our learning:

  1. Anki’s Built-in Stats: Provides a basic overview of reviews.

  2. The FSRS Helper/Optimizer: Not only does it optimize scheduling, but it also generates data on card Stability and Difficulty.

  3. Individual Card Info: Pressing the i shortcut (or Shift+Ctrl+I) during review shows the detailed history of a single card.

  4. Community Add-ons: Plugins like Search Stats Extended .

Currently, these data sources are fragmented. A user needs to act as a “data detective,” switching between different interfaces to interpret and synthesize this information to judge their card quality.

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this sure seems like a lot a lot of work for a small triangle literally everyone would either ignore or be incredibly annoyed by.

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You’re right, if the end result is just an annoying, insignificant icon, then it’s definitely not worth a massive development effort.

However, I’d like to clarify that the “small triangle” was just a simple example I used for the sake of description; it’s not the core of my proposal.

My core idea is about solving a deeper problem: Anki has a wealth of powerful but fragmented data, and we lack an effective way to use it to evaluate the quality of our learning material.

We have FSRS S/D values, lapse counts, review histories, and more, but they are all scattered. It’s very difficult for a user, especially a newcomer, to connect these data points to answer the question, “Am I making good cards?”

And this is arguably the most critical part of using Anki effectively. From my experience (and the consensus of many veteran users), if card quality is low, Anki’s effectiveness plummets, leading to the “Garbage In, Garbage Out” dilemma. In that scenario, using Anki can be even less efficient than traditional study methods.

So, the system I’m proposing is essentially a “diagnostic engine” that integrates data . The final user interface is completely open for discussion—it could be a dedicated “Deck Health Report” page, an extra “Health Score” column in the browser for sorting, or even have no UI at all and just provide an API for other add-on developers.

The main point is to turn data into actionable insights , helping users identify and improve the low-quality cards that are wasting their time. I believe solving this problem would be incredibly valuable for improving Anki’s overall learning efficiency and user experience.

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If the settings are customizable, then how will the users know what to set them to? It just adds a new layer of complexity. Users use Anki for all sorts of reasons, which can make different cards have different times, as well as fatigue influencing times, and being AFK.

And making good cards can also be about how you use the Extra field, and how you use other features like cloze hints or image occlusion cards, which are very flexible and thus have their own skill level in card creation. These things would not be evaluated by the card health report, which is a massive flaw for a feature that’s supposed to help users make good quality cards.

I just don’t think a possible implementation exists that would benefit new users, who are the main target audience for this feature. If they don’t know what a “good” card is, they won’t know what a personalized card health report settings would look like either. And if they did know what these personalized settings were, then why would they need this report in the first place if they’ve already cognitively justified adding cards that may violate them?

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