naija-faker-mcp

Generate marital status

generate_marital_status

Read-only

Generate a synthetic marital status for fake Nigerian profiles. Provide an age to exclude statuses that are implausible for that age.

Instructions

Generates a synthetic marital status. Pass an age to rule out statuses implausible for it.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

Name	Required	Description	Default
`age`	No

Output Schema

Name	Required	Description	Default
`value`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv2.1.0Sep 23, 2026

addedInput schema / $schema

Added value: +"http://json-schema.org/draft-07/schema#"

addedInput schema / properties / age

Added value: +{
+  "maximum": 9007199254740991,
+  "minimum": 0,
+  "type": "integer"
+}

Changed1 schema field changedv2.0.0Sep 16, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "value": {}
+  },
+  "required": [
+    "value"
+  ],
+  "type": "object"
+}

First observedv1.0.1Sep 13, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context beyond annotations: the result is synthetic and age-dependent, implying a constrained random generation.

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 no filler; the core action and the key usage nuance are front-loaded. Every sentence earns its place.

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?

For a simple generator with an output schema present, the description covers the main invocation concern (age filtering). A minor gap is that it does not explicitly state what happens when age is omitted, even though the parameter is optional.

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 coverage is 0%, so the description must compensate for the age parameter's meaning. It explains that age is used to rule out implausible statuses, giving semantic value beyond the schema's bare integer range. It does not fully spell out edge cases or default behavior when age is omitted, but the intent is clear.

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?

States a specific verb ('Generates') and resource ('synthetic marital status'), which clearly identifies the tool's function among many generate_* siblings. The second sentence adds the age-based filtering behavior, further distinguishing it from sibling generators.

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?

Provides clear context: pass an age to rule out implausible statuses, which implicitly tells the agent how to use the tool effectively. It does not explicitly name alternatives or exclusions, but the sibling set is large and homogeneous, so this level of guidance is reasonable.

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