diff --git a/docs/dotprompt.md b/docs/dotprompt.md
index 034d27896..c94d94458 100644
--- a/docs/dotprompt.md
+++ b/docs/dotprompt.md
@@ -157,31 +157,31 @@ You can set the format and output schema of a prompt to coerce into JSON:
 model: vertexai/gemini-1.0-pro
 input:
   schema:
-    location: string
+    theme: string
 output:
   format: json
   schema:
     name: string
-    hitPoints: integer
-    description: string
+    price: integer
+    ingredients(array): string
 ---
 
-Generate a tabletop RPG character that would be found in {{location}}.
+Generate a menu item that could be found at a {{theme}} themed restaurant.
 ```
 
 When generating a prompt with structured output, use the `output()` helper to
 retrieve and validate it:
 
 ```ts
-const characterPrompt = await prompt('create_character');
+const createMenuPrompt = await prompt('create_menu');
 
-const character = await characterPrompt.generate({
+const menu = await createMenuPrompt.generate({
   input: {
-    location: 'the beach',
+    theme: 'banana',
   },
 });
 
-console.log(character.output());
+console.log(menu.output());
 ```
 
 ## Multi-message prompts
@@ -201,8 +201,8 @@ input:
 ---
 
 {{role "system"}}
-You are a helpful AI assistant that really loves to talk about puppies. Try to work puppies
-into all of your conversations.
+You are a helpful AI assistant that really loves to talk about food. Try to work
+food items into all of your conversations.
 {{role "user"}}
 {{userQuestion}}
 ```
diff --git a/docs/evaluation.md b/docs/evaluation.md
index 82b61f09c..b080d6e88 100644
--- a/docs/evaluation.md
+++ b/docs/evaluation.md
@@ -34,14 +34,18 @@ Note: The configuration above requires installing the `@genkit-ai/evaluator` and
 Start by defining a set of inputs that you want to use as an input dataset called `testQuestions.json`. This input dataset represents the test cases you will use to generate output for evaluation.
 
 ```json
-["How old is Bob?", "Where does Bob lives?", "Does Bob have any friends?"]
+[
+  "What is on the menu?",
+  "Does the restaurant have clams?",
+  "What is the special of the day?"
+]
 ```
 
 You can then use the `eval:flow` command to evaluate your flow against the test
 cases provided in `testQuestions.json`.
 
 ```posix-terminal
-genkit eval:flow bobQA --input testQuestions.json
+genkit eval:flow menuQA --input testQuestions.json
 ```
 
 You can then see evaluation results in the Developer UI by running:
@@ -55,7 +59,7 @@ Then navigate to `localhost:4000/evaluate`.
 Alternatively, you can provide an output file to inspect the output in a json file.
 
 ```posix-terminal
-genkit eval:flow bobQA --input testQuestions.json --output eval-result.json
+genkit eval:flow menuQA --input testQuestions.json --output eval-result.json
 ```
 
 Note: Below you can see an example of how an LLM can help you generate the test
@@ -167,7 +171,7 @@ genkit eval:run customLabel_dataset.json
 To output to a different location, use the `--output` flag.
 
 ```posix-terminal
-genkit eval:flow bobQA --input testQuestions.json --output customLabel_evalresult.json
+genkit eval:flow menuQA --input testQuestions.json --output customLabel_evalresult.json
 ```
 
 To run on a subset of the configured evaluators, use the `--evaluators` flag and provide a comma separated list of evaluators by name: