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Api Ninjas

by io.github.pipeworx-io
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Animals

animals
Read-onlyIdempotent

API Ninjas animals: facts about an animal species by name. Returns a list of { name, taxonomy, locations, diet, habitat, lifespan, top_speed }. Example: animals({ name: "cheetah" }).

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "cheetah"
    },
    "name": "animals"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesAnimal name to look up, e.g. 'cheetah', 'lion'
_apiKeyNoOptional — your own API Ninjas key for higher limits; omit to use the shared Pipeworx key.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare read-only/idempotent/non-destructive behavior, so the safety profile is covered. The description adds the external API Ninjas provenance and, since there is no output schema, the concrete return shape (list of name, taxonomy, locations, diet, habitat, lifespan, top_speed). It does not address rate limits or error behavior, but these are not essential for this simple read-only lookup.

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?

Compact and front-loaded: purpose, return fields, and an example with no filler. Every sentence earns its place, and the most important usage detail (lookup by name) appears immediately.

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?

For a one-required-parameter read-only lookup, the description provides enough: input example, output fields, and data source. The optional API key nuance is already captured in the schema, and because no output schema exists, the explicit field list completes the picture.

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 coverage is 100%; both name and _apiKey have descriptions, including an example for name. The description's 'by name' and cheetah example echo that schema rather than adding new meaning. Baseline 3 applies because the schema carries the parameter semantics.

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?

Opens with a specific verb+resource: 'facts about an animal species by name'. It names the exact returned fields, so an agent can identify it as a direct animal-fact lookup rather than a research or comparison tool. The example appends a concrete invocation, removing ambiguity.

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?

No explicit when/when-not guidance or alternative tool names appear. The phrase 'by name' and the cheetah example imply that this tool is for fetching facts by species name, but an agent is left to infer when to choose it over broad research tools like deep_research or entity_profile.

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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