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Glama

Dummyjson

by io.github.pipeworx-io

Recipe

recipe
Read-onlyIdempotent

Fetch a single fake recipe by numeric id from DummyJSON. Returns name, ingredients, instructions, prep/cook time, servings, difficulty, and cuisine.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoRecipe ID
nameNoRecipe name
tagsNoRecipe tags
imageNoRecipe image URL
ratingNoRecipe rating
userIdNoUser ID of recipe author
cuisineNoCuisine type
servingsNoNumber of servings
difficultyNoDifficulty level
ingredientsNoList of ingredients
reviewCountNoNumber of reviews
instructionsNoCooking instructions
cookTimeMinutesNoCook time in minutes
prepTimeMinutesNoPrep time in minutes
caloriesPerServingNoCalories per serving

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "id": 1
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "caloriesPerServing": {
+      "description": "Calories per serving",
+      "type": "number"
+    },
+    "cookTimeMinutes": {
+      "description": "Cook time in minutes",
+      "type": "number"
+    },
+    "cuisine": {
+      "description": "Cuisine type",
+      "type": "string"
+    },
+    "difficulty": {
+      "description": "Difficulty level",
+      "type": "string"
+    },
+    "id": {
+      "description": "Recipe ID",
+      "type": "number"
+    },
+    "image": {
+      "description": "Recipe image URL",
+      "type": "string"
+    },
+    "ingredients": {
+      "description": "List of ingredients",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "instructions": {
+      "description": "Cooking instructions",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "name": {
+      "description": "Recipe name",
+      "type": "string"
+    },
+    "prepTimeMinutes": {
+      "description": "Prep time in minutes",
+      "type": "number"
+    },
+    "rating": {
+      "description": "Recipe rating",
+      "type": "number"
+    },
+    "reviewCount": {
+      "description": "Number of reviews",
+      "type": "number"
+    },
+    "servings": {
+      "description": "Number of servings",
+      "type": "number"
+    },
+    "tags": {
+      "description": "Recipe tags",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "userId": {
+      "description": "User ID of recipe author",
+      "type": "number"
+    }
+  },
+  "type": "object"
+}
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. Description adds behavioral context: it fetches fake data from DummyJSON and returns specific fields, which is valuable beyond annotations. No contradictions.

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?

Single sentence, no wasted words, front-loaded with action and returns. Efficient and clear.

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

Completeness5/5

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

Given the tool has an output schema (so return details are covered), one parameter, and annotations indicating safe read, the description fully covers purpose, behavior, and parameter meaning. No gaps for the given complexity.

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

Parameters4/5

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

Schema description coverage is 0% but description compensates by specifying 'numeric `id` from DummyJSON', giving context about the parameter meaning and source. For a single parameter, this provides sufficient semantics beyond the schema type.

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?

Description clearly states it fetches a single fake recipe by numeric ID, listing returned fields (name, ingredients, instructions, etc.). This specifies the verb ('Fetch'), resource ('single fake recipe'), and key attributes, distinguishing it from sibling 'recipes' which likely fetches multiple.

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?

Implies usage for fetching one recipe by ID, but does not explicitly state when to use this vs alternatives like 'recipes'. No direct mention of when-not or alternative tools, leaving the agent to infer from sibling names.

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

All Dummyjson toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Many tools have overlapping purposes, e.g., multiple tools for data retrieval (ask_pipeworx, ask_pipeworx_grounded, deep_research, entity_profile) that differ only in nuance, and the inclusion of both DummyJSON and Pipeworx tools creates confusion about which domain to use for what. Agents will struggle to select the correct tool.

Naming Consistency2/5

Naming conventions are mixed: Pipeworx tools use diverse patterns (verb_noun like 'validate_claim', noun like 'entity_profile', verb like 'forget'), while DummyJSON tools use simple nouns (posts, comments). No consistent pattern across the set.

Tool Count2/5

43 tools is excessive for a server named 'Dummyjson'. The majority are Pipeworx tools unrelated to fake data, making the set feel bloated and unfocused. The count is too large for the apparent scope.

Completeness3/5

For a fake data API, the set is incomplete: it only provides read operations (fetch, search) with no create, update, or delete capabilities. However, for the Pipeworx portion, the read coverage is extensive, so it's not severely lacking overall.

Resources