qr-maker

list_links

View and manage short links with click analytics. Track link performance through paginated lists showing code, target URL, status, and creation date.

Instructions

List tracked short links with click counts. Supports cursor pagination. Returns code, target URL, status, and creation date for each link.

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": "list_links"
  }
}

Input Schema

Name	Required	Description	Default
`cursor`	No	Pagination cursor from previous response
`limit`	No	Number of links per page (1-100). Default: 25.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Apr 13, 2026

TDQS

A4/5.0

Behavior4/5

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

With no annotations provided, the description carries full burden and adds valuable behavioral context: it discloses that the tool supports cursor pagination (a key operational trait) and returns specific fields (code, target URL, status, creation date). However, it doesn't mention rate limits, authentication needs, or whether it's read-only (implied but not explicit).

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 front-loaded with the core purpose in the first sentence, followed by pagination support and return fields in subsequent sentences. Each sentence adds value with zero waste, making it appropriately sized and well-structured for quick comprehension.

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 list tool with no annotations and no output schema, the description is reasonably complete: it covers purpose, pagination behavior, and return fields. However, it lacks details on error conditions, default ordering, or whether click counts are real-time/historical, leaving minor gaps given the tool's moderate complexity.

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 the schema fully documents the two parameters (cursor and limit). The description adds no parameter-specific information beyond what's in the schema, but doesn't need to compensate for gaps. Baseline 3 is appropriate as 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?

The description clearly states the verb 'List' and resource 'tracked short links with click counts', distinguishing it from siblings like get_link (single link) or get_link_analytics (detailed analytics). It specifies the scope as listing all tracked links with metrics, making the purpose specific and differentiated.

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?

The description implies usage for listing links with click counts, but provides no explicit guidance on when to use this versus alternatives like get_link (for a single link) or get_link_analytics (for detailed analytics). It mentions cursor pagination, which hints at use for large datasets, but lacks clear when/when-not statements or named alternatives.

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