> ## Documentation Index > Fetch the complete documentation index at: https://docs.learningcommons.org/llms.txt > Use this file to discover all available pages before exploring further. # Introduction > Overview of Graphics evaluators that check the images in instructional content, from whether a math graphic is correct to how complex a text's graphics are. ## The problem AI tools now generate many of the graphics students see: charts, maps, diagrams, geometry figures, and worked solutions. Most checks on generated content read only the text, so a graphic passes through unexamined. A graphic can fail a student in two ways: * **It's wrong.** A miscounted feature, a mislabeled axis, or a flawed step can look right at a glance and still teach the wrong thing. * **It's too hard to read.** A passage can sit on grade level on every language measure, yet put its key idea in a graphic that students at that grade haven't learned to read, like a dual-axis graph. At the volume AI produces, no team can review every graphic by hand. Research shows that graphics help students learn when they carry information relevant to the text, not when they decorate it ([Levie & Lentz, 1982](https://doi.org/10.1007/BF02765184) ↗), and only when readers connect what they see with what they read ([Hannus & Hyönä, 1999](https://doi.org/10.1006/ceps.1998.0987) ↗; [Mason et al., 2013](https://doi.org/10.1016/j.compedu.2012.07.011) ↗). Reading a graphic is also a skill in its own right: the same display can be clear to one reader and opaque to another, depending on what each knows about how that kind of graphic works ([Shah & Hoeffner, 2002](https://doi.org/10.1023/A:1013180410169) ↗). That barrier falls hardest on students with less exposure to graph and diagram conventions. ## What we're building Each Graphics evaluator takes images as input, assesses a different aspect of the graphics in instructional content, and returns its reasoning, so you can see what to fix and not just whether something's wrong. | Evaluator | Subject | Grades | Description | | :- | :- | :- | :- | | **[Graphics Accuracy](/evaluators/graphics-evaluators/graphics-accuracy)** | Math | K–12 | Checks whether a math graphic correctly shows what its accompanying text states | | **[Graphics Complexity](/evaluators/graphics-evaluators/graphics-complexity)** | ELA | 3–12 | Assesses how much a text's graphics add to its reading complexity for students at a given grade level | The Graphics evaluators accept PNG, JPEG, and WebP images. Images go directly from your environment to the model provider, using your own API key, and are never sent to Learning Commons. ## Use cases * **Check graphics before they reach students:** Run generated graphics through an evaluator. When it flags a graphic as incorrect, or as more complex than you intended for the grade, send that graphic to be regenerated or reviewed by a person. * **Find problems at the source:** Look across the graphics an evaluator flagged as incorrect or too complex for recurring issues, like misread axes or key content that appears only in a graphic, and fix the prompt that produced them. * **Match graphics to instructional goals:** Use an evaluator's complexity rating to check whether a graphic fits your instructional goal: simple enough to support reading the prose, or demanding enough to teach students to read and integrate visual information. * **Monitor changes over time:** Compare results across model updates or prompt changes to catch shifts in the graphics your product generates. ## Limitations Graphics evaluator outputs should not be used for high-stakes applications like grading, assessment, or placement decisions without human review. Remember that LLM outputs can vary across runs, especially on borderline cases. We recommend keeping a human in the loop and treating outputs as directional signals vs. definitive judgments. | Limitation | Details | | :- | :- | | **Static images only** | Animated graphics aren't supported. Interactive graphics are evaluated from a single screenshot | | **Image as submitted** | Results reflect the image you submit. A cropped, low-resolution, or partial image can change the result | ## Related topics Explore evaluators that assess the qualitative complexity of a text's prose. Explore evaluators that assess content alignment to academic standards. Run an evaluator in the Evaluators playground, a Python notebook, or with the SDK.