Skip to main content
Glama

salsa_risk_assessment

Assess gastrointestinal risk based on salsa selection, spice tolerance, and recent meals to inform safer Chipotle orders.

Instructions

Predicts the gastrointestinal consequences of your salsa choices. Consult your doctor before using this tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
salsasYesWhich salsas are you getting?
spice_toleranceYesYour spice tolerance level
has_eaten_todayYesHave you eaten anything else today?

Implementation Reference

  • The 'salsa_risk_assessment' tool is registered and implemented in index.js. It takes a list of salsas, spice tolerance, and eaten status as input, calculates a heat score, and returns a formatted markdown summary.
    server.tool(
      "salsa_risk_assessment",
      "Predicts the gastrointestinal consequences of your salsa choices. Consult your doctor before using this tool.",
      {
        salsas: z
          .array(z.enum(["mild", "medium_green", "medium_corn", "hot"]))
          .min(1)
          .describe("Which salsas are you getting?"),
        spice_tolerance: z.enum(["low", "medium", "high", "texas"]).describe("Your spice tolerance level"),
        has_eaten_today: z.boolean().describe("Have you eaten anything else today?"),
      },
      async ({ salsas, spice_tolerance, has_eaten_today }) => {
        const scoville = {
          mild: 500, medium_green: 2500, medium_corn: 1500, hot: 15000,
        };
        const totalScoville = salsas.reduce((sum, s) => sum + scoville[s], 0);
    
        const toleranceMultiplier = { low: 2.0, medium: 1.0, high: 0.5, texas: 0.2 }[spice_tolerance];
        const emptyStomachPenalty = has_eaten_today ? 1.0 : 1.8;
    
        const adjustedHeat = totalScoville * toleranceMultiplier * emptyStomachPenalty;
    
        let spiceRisk, milkGlasses, regretProbability;
        if (adjustedHeat > 20000) {
          spiceRisk = "SEVERE";
          milkGlasses = 3;
          regretProbability = "95%";
        } else if (adjustedHeat > 10000) {
          spiceRisk = "HIGH";
          milkGlasses = 2;
          regretProbability = "70%";
        } else if (adjustedHeat > 4000) {
          spiceRisk = "MODERATE";
          milkGlasses = 1;
          regretProbability = "35%";
        } else {
          spiceRisk = "LOW";
          milkGlasses = 0;
          regretProbability = "10%";
        }
    
        const lines = [
          "# Salsa Risk Assessment",
          "",
          "```",
          "  Gastrointestinal Impact Analysis",
          "  =================================",
          `  Salsas Selected:     ${salsas.join(", ")}`,
          `  Combined Scoville:   ${totalScoville} SHU`,
          `  Tolerance Level:     ${spice_tolerance}`,
          `  Empty Stomach:       ${!has_eaten_today ? "YES (danger)" : "No"}`,
          `  Adjusted Heat Index: ${adjustedHeat.toFixed(0)} AHU`,
          "",
          `  SPICE RISK:          ${spiceRisk}`,
          `  Recommended Milk:    ${milkGlasses} glass(es)`,
          `  Regret Probability:  ${regretProbability}`,
          "```",
          "",
          ...(spiceRisk === "SEVERE"
            ? [
                "> WARNING: You are entering the salsa danger zone.",
                "> Side effects may include: involuntary tears, existential reflection, and texting your ex.",
              ]
            : []),
          ...(spiceRisk === "LOW" ? ["> Your ancestors are watching. They are not impressed."] : []),
          ...(spice_tolerance === "texas"
            ? ["> Texas-level tolerance detected. Nothing can hurt you anymore."]
            : []),
        ];
    
        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 full burden. It discloses the predictive nature of the operation and adds crucial medical context via the doctor consultation warning. However, it omits details about data persistence, calculation methodology, or specific output format.

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?

Two sentences with zero waste. The first sentence front-loads the purpose; the second provides necessary medical disclaimer. Every word earns its place with no repetition of structured data.

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

Completeness4/5

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

Appropriately complete for a 3-parameter tool with 100% schema coverage and no output schema. The medical disclaimer adds necessary safety context for a health-adjacent prediction tool, though it could briefly characterize the prediction output (e.g., risk level vs detailed report).

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% (all 3 parameters have descriptions). The description references 'your salsa choices' aligning with the salsas parameter but does not add semantic detail 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?

Clear specific verb 'Predicts' with defined scope 'gastrointestinal consequences of your salsa choices'. Uniquely distinguishes from sibling ordering/nutrition tools by focusing on health risk assessment rather than food selection or nutritional data.

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?

Implied usage through the specific health domain ('gastrointestinal consequences', 'consult your doctor'), suggesting use when evaluating spice-related health risks. Lacks explicit comparison to siblings like get_nutrition_facts or when-not guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/YoshiSaurus/mcp-otle'

If you have feedback or need assistance with the MCP directory API, please join our Discord server