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User-Agent parser

user_agent
Read-onlyIdempotent

Parses a User-Agent string into browser and version, operating system and version, device type, and whether it looks like a bot.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uaYesUser-Agent string to parse. Required over MCP: the server cannot see the end user's own User-Agent.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / ua / description
      Previous value: -"User-Agent string to parse. If omitted, the request's own User-Agent header is parsed instead."New value: +"User-Agent string to parse. Required over MCP: the server cannot see the end user's own User-Agent."
    • changedInput schema / required
      Previous value: -[]New value: +[
      +  "ua"
      +]
  2. Changed1 schema field changed
    • changedInput schema / properties / ua / description
      Previous value: -""New value: +"User-Agent string to parse. If omitted, the request's own User-Agent header is parsed instead."
  3. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description usefully discloses the shape of the result (browser, OS, device type, bot flag), which matters because there is no output schema, but it says nothing about behavior on malformed or unparseable input strings.

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?

A single front-loaded sentence with zero filler; every clause names a distinct output field.

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 one-parameter pure-function tool with no output schema, naming the returned fields is the key missing piece and it is present. The only residual gap is error/edge-case behavior for malformed UA strings.

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?

One parameter with 100% schema description coverage, so the baseline is 3. The description adds no format, syntax, or example detail beyond what the schema already documents.

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 (parses) and resource (User-Agent string) and enumerates exactly what is extracted: browser+version, OS+version, device type, bot likelihood. No sibling tool overlaps, so differentiation is not needed and none is required.

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

Usage Guidelines2/5

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

There is no statement of when to use this tool versus alternatives, no prerequisites, and no exclusions. The only contextual hint lives in the input schema's own description (the server cannot see the caller's UA), not in the tool description.

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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