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Glama

dogsapi

by io.github.pipeworx-io

Get Breed

get_breed
Read-onlyIdempotent

Get detailed info about a dog breed by ID. Returns characteristics, temperament, origin, size, and health data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe breed ID (obtained from list_breeds)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesUnique breed identifier
nameYesBreed name
descriptionYesBreed description
hypoallergenicYesWhether breed is hypoallergenic
male_weight_kgYesMale weight range
life_span_yearsYesLife span range
female_weight_kgYesFemale weight range

Schema Changelog

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

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "description": {
+      "description": "Breed description",
+      "type": "string"
+    },
+    "female_weight_kg": {
+      "description": "Female weight range",
+      "properties": {
+        "max": {
+          "description": "Maximum weight in kg",
+          "type": "number"
+        },
+        "min": {
+          "description": "Minimum weight in kg",
+          "type": "number"
+        }
+      },
+      "required": [
+        "min",
+        "max"
+      ],
+      "type": "object"
+    },
+    "hypoallergenic": {
+      "description": "Whether breed is hypoallergenic",
+      "type": "boolean"
+    },
+    "id": {
+      "description": "Unique breed identifier",
+      "type": "string"
+    },
+    "life_span_years": {
+      "description": "Life span range",
+      "properties": {
+        "max": {
+          "description": "Maximum lifespan in years",
+          "type": "number"
+        },
+        "min": {
+          "description": "Minimum lifespan in years",
+          "type": "number"
+        }
+      },
+      "required": [
+        "min",
+        "max"
+      ],
+      "type": "object"
+    },
+    "male_weight_kg": {
+      "description": "Male weight range",
+      "properties": {
+        "max": {
+          "description": "Maximum weight in kg",
+          "type": "number"
+        },
+        "min": {
+          "description": "Minimum weight in kg",
+          "type": "number"
+        }
+      },
+      "required": [
+        "min",
+        "max"
+      ],
+      "type": "object"
+    },
+    "name": {
+      "description": "Breed name",
+      "type": "string"
+    }
+  },
+  "required": [
+    "id",
+    "name",
+    "description",
+    "life_span_years",
+    "male_weight_kg",
+    "female_weight_kg",
+    "hypoallergenic"
+  ],
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "id": "golden-retriever"
+  },
+  {
+    "id": "labrador-retriever"
+  }
+]
  3. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, covering the safety profile. The description adds behavioral context by listing what data is returned (characteristics, temperament, origin, size, health data), which is useful and not redundant with annotations.

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?

One clear, front-loaded sentence that communicates purpose and return fields without unnecessary detail. Every word earns its place.

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?

The tool is simple with one parameter and an output schema. The description states the key returned categories, and with the output schema present, no further explanation of return structure is needed. The context is fully adequate.

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 100% for the single 'id' parameter. The description adds value by explaining the parameter's provenance ('obtained from list_breeds'), which aids correct usage beyond the schema's bare description.

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 clearly states 'Get detailed info about a dog breed by ID', identifying the specific action and resource. It distinguishes itself from the sibling 'list_breeds' by indicating this retrieves a single breed's details rather than a list.

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

Usage Guidelines4/5

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

The description implies usage context by specifying 'by ID' and the parameter schema adds 'obtained from list_breeds', which tells the agent the prerequisite step. However, it does not explicitly state alternatives or when not to use it, but the guidance is sufficient for a simple lookup.

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

All dogsapi toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Several tools have genuinely unclear boundaries: ask_pipeworx and ask_pipeworx_beta are described as currently identical, ask_pipeworx_grounded shares the same router, and the polymarket_edges/arbitrage/fill_risk/bet_research group overlaps heavily in purpose. The remaining clusters (dog data, memory, subscriptions) are mostly distinct, so the confusion is concentrated in a few spots but severe there.

Naming Consistency3/5

Nearly all names are lower_snake_case and readable, but the conventions are mixed: get_/list_/ask_/scan_ verb-noun names sit alongside bare verbs (remember, forget, recall), noun-phrase names (entity_profile, bet_research, pipeworx_trending), and a versioned suffix (ask_pipeworx_beta). No single predictable pattern covers the whole set.

Tool Count2/5

At 35 tools, the server is well past the 25+ threshold for feeling bloated, and the count is dominated by unrelated Pipeworx, prediction-market, and AI-visibility tools rather than the dog-data domain implied by 'dogsapi'. Only four tools actually serve the dog API, making the surface both oversized and misaligned with the server name.

Completeness3/5

The broad data-access side is thorough, covering discovery, universal routing, grounded answers, deep research, entity profiles, comparisons, claim validation, memory, and subscriptions. However, the nominal dog domain is thin (list/get/groups/facts with no filtering or additional operations), subscriptions have no update path, and some one-off tools like generate_llms_txt and scan_dependency exist without any surrounding lifecycle.

Resources