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chipotle_personality_test

Analyze your Chipotle order preferences to determine your eating personality type based on protein choice, guacamole frequency, entree format, and chip habits.

Instructions

Scientifically determines what kind of Chipotle eater you are based on your order preferences.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
go_to_proteinYesYour usual protein
guac_frequencyYesHow often do you get guac?
entree_formatYesYour usual format
chipsYesDo you always get chips?

Implementation Reference

  • Registration and implementation of the 'chipotle_personality_test' tool, including input schema and the handler that calculates the personality type based on inputs.
    server.tool(
      "chipotle_personality_test",
      "Scientifically determines what kind of Chipotle eater you are based on your order preferences.",
      {
        go_to_protein: z.enum(PROTEINS).describe("Your usual protein"),
        guac_frequency: z.enum(["always", "sometimes", "never"]).describe("How often do you get guac?"),
        entree_format: z.enum(["Burrito", "Bowl", "Tacos (3)", "Salad"]).describe("Your usual format"),
        chips: z.boolean().describe("Do you always get chips?"),
      },
      async ({ go_to_protein, guac_frequency, entree_format, chips }) => {
        // Personality matrix
        let type, traits;
    
        if (guac_frequency === "always" && chips) {
          type = "The Guac Maximalist";
          traits = [
            "Financially irresponsible",
            "Emotionally fulfilled",
            "Orders chips & guac every single time",
            "Has never once looked at the total before paying",
            "Main character energy",
          ];
        } else if (entree_format === "Bowl" && go_to_protein === "Chicken") {
          type = "The Optimizer";
          traits = [
            "Tracks macros in a spreadsheet",
            "Bowl because 'you get more food'",
            "Has strong opinions about rice-to-protein ratio",
            "Orders online to avoid human interaction",
            "Probably in tech",
          ];
        } else if (go_to_protein === "Steak" || go_to_protein === "Barbacoa") {
          type = "The Premium Player";
          traits = [
            "Only orders premium proteins",
            "Refers to Chipotle as 'fast casual dining'",
            "Tips well",
            "Has a Chipotle rewards tier they're proud of",
            "Judges people who get sofritas",
          ];
        } else if (go_to_protein === "Sofritas") {
          type = "The Enlightened One";
          traits = [
            "Plant-based and wants you to know about it",
            "Has called Chipotle 'actually pretty sustainable'",
            "Orders a water cup",
            "Genuinely enjoys cauliflower rice",
            "Brings their own bag",
          ];
        } else if (entree_format === "Tacos (3)") {
          type = "The Wildcard";
          traits = [
            "Lives on the edge",
            "Orders tacos at a burrito restaurant",
            "Thinks 3 tacos is enough (it's not)",
            "Probably double wraps",
            "Unpredictable in all areas of life",
          ];
        } else if (entree_format === "Salad") {
          type = "The Contrarian";
          traits = [
            "Orders a salad at Chipotle",
            "Has told friends 'it's actually really healthy'",
            "Secret menu knowledge",
            "Eats the crispy bowl shell last",
            "Controlled chaos",
          ];
        } else if (guac_frequency === "never") {
          type = "The Ascetic";
          traits = [
            "Has never paid for guac",
            "Brings a budget to Chipotle",
            "Meal preps with Chipotle bowls",
            "Knows the exact calorie count",
            "Respectable but concerning",
          ];
        } else {
          type = "The Regular";
          traits = [
            "Solid, dependable order",
            "The backbone of Chipotle's revenue",
            "Never complains, never innovates",
            "Orders the same thing every time",
            "Would describe themselves as 'easy going'",
          ];
        }
    
        const lines = [
          "# Chipotle Personality Assessment",
          "",
          `## You are: **${type}**`,
          "",
          "### Traits:",
          ...traits.map((t) => `- ${t}`),
          "",
          "---",
          `*Based on: ${go_to_protein}, ${entree_format}, guac=${guac_frequency}, chips=${chips}*`,
          "",
          "> This assessment is peer-reviewed and published in the Journal of Burrito Psychology.",
        ];
    
        return { content: [{ type: "text", text: lines.join("\n") }] };
      }
    );
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full disclosure burden. It establishes that the tool returns a personality classification ('what kind of Chipotle eater you are'), providing basic behavioral context. However, it omits side effects, data persistence, whether results are deterministic, or any rate limiting concerns.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. 'Scientifically' and 'what kind of Chipotle eater you are' front-load the value proposition immediately, and every word contributes to understanding the tool's whimsical analytical purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the input schema is fully documented, the absence of an output schema creates a gap the description doesn't fill. It states the tool 'determines' a personality type but doesn't describe the return format (string, object, category), confidence levels, or whether results include explanations. Given 4 required parameters and no annotations, additional output specification would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, documenting all four parameters ('Your usual protein', 'How often do you get guac?', etc.). The description aggregates these as 'order preferences' but adds no additional syntax details, constraints, or interdependencies beyond what the schema already provides, warranting the baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('determines') and clearly identifies the resource (Chipotle eater personality type). It effectively distinguishes this analytical/entertainment tool from functional siblings like 'place_order', 'check_order_status', and 'build_entree' by focusing on preference analysis rather than transactional operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage through the phrase 'based on your order preferences', suggesting it's for analyzing ordering habits. However, it lacks explicit guidance on when to select this versus analytical siblings like 'optimize_guac_roi' or 'bowl_vs_burrito_decision_engine'. No exclusions or prerequisites are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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