AutoRank MCP

build_utm_link

Generate UTM-tagged URLs for tracking marketing campaigns. Specify source, medium, and campaign to append analytics parameters to any URL.

Instructions

Build a UTM-tagged tracking URL.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>",
      "source": "<source>",
      "medium": "<medium>",
      "campaign": "<campaign>"
    },
    "name": "build_utm_link"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes
`term`	No
`medium`	Yes
`source`	Yes
`content`	No
`campaign`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 2, 2026

TDQS

B3.3/5.0

Behavior3/5

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

With no annotations, the description carries the full burden of disclosing behavior. It states the core action of building a UTM-tagged URL, which implies a non-destructive operation, but it does not disclose any additional behavioral traits such as validation rules, how parameters are appended, or potential side effects. The description is not misleading, but it is minimal.

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?

The description is a single, front-loaded sentence with no extraneous words. Every word earns its place, and it is immediately scannable. It is appropriately concise for a simple builder tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 6 parameters (4 required) and no annotations, the description is too sparse to be fully contextual. It does not explain what constitutes a valid 'url', how the UTM parameters relate to the final output, or any constraints. Although an output schema exists, the input semantics remain uncovered, making this description incomplete for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for explaining parameters. The phrase 'UTM-tagged' hints at the standard UTM parameters (source, medium, campaign, etc.), but it does not explicitly define the 'url', 'term', 'content', or their roles. The description adds minimal meaning beyond the raw schema, leaving the agent to rely on domain knowledge.

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 uses a specific verb ('Build') and a clear resource ('UTM-tagged tracking URL'), which distinctly identifies the tool's function and differentiates it from sibling tools focused on titles, meta tags, robots, and schema. It is immediately clear what this tool does.

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?

The description provides no context on when to use this tool versus alternatives, no prerequisites, and no exclusion criteria. It simply states the function without guiding the agent on decision-making, leaving the agent to infer appropriate usage from the tool name alone.

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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