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Generate fictional US SSN-style identifiers

generate-ssn
Read-onlyIdempotent

Generate fictional US SSN-style test identifiers. Use for SSN test fields; use generate-fake-data for mixed-record fixtures. Returns a string for count=1, otherwise an array; structural validity does not confirm issuance.

Input Schema

NameRequiredDescriptionDefault
seedNoOptional deterministic seed for repeatable fake identifiers.
countNoNumber of synthetic SSN-style fixtures, 1–8.
validNoWhether fixtures should pass the generator's structural validity rules, not actual issuance checks.
formattedNoWhether to add standard dashes to the generated identifier.

Schema Changelog

Changes observed during successful MCP inspections.

  1. 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 readOnly, idempotent, closed-world and non-destructive, so the safety profile is covered. The description adds real value beyond that: it discloses the return-shape polymorphism ('string for count=1, otherwise an array') and warns that structural validity does not confirm issuance. It does not mention determinism behavior when seed is supplied, which would have made this a 5.

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?

Three short sentences, zero filler, with purpose front-loaded and the sibling routing and return-shape caveats following in priority order. Every sentence 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?

There is no output schema, so the description correctly compensates by stating the return shape (string vs array). Combined with the annotations covering safety and the fully documented schema, an agent has everything needed to call this correctly.

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%, so all four parameters (seed, count, valid, formatted) are already documented in the schema, and the description adds no parameter-level syntax or format detail. It only indirectly touches count via the return-shape note. Baseline 3 applies when the schema does the heavy lifting.

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 and resource ('Generate fictional US SSN-style test identifiers') that is unambiguous and immediately distinguishable from siblings like generate-fake-data and generate-phone-number. The scope is narrowed to test fixtures rather than real data, which an agent can act on without opening the schema.

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

Usage Guidelines5/5

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

Explicitly names the alternative ('use generate-fake-data for mixed-record fixtures') and the condition that selects it, giving both when-to-use and when-to-use-something-else. Nothing is left to inference.

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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