Lounge Frog

Best credit cards for a kind of spending

best_credit_cards

Read-onlyIdempotent

Points Frog's ranking of popular US rewards cards for one kind of spending (dining, groceries, flights, hotels, gas, streaming, everyday spending, or no annual fee): cents back per dollar, which is the card's earning rate times Points Frog's value for its points (cash back at 1 cent), with each card's rate, annual fee, caps and notes from the issuer's terms, the list's page and the calculator that ranks cards on someone's own spending. Welcome bonuses and credits are left out.

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": {
      "category": "<category>"
    },
    "name": "best_credit_cards"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	Max cards (default 10)
`category`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 5, 2026

TDQS

A3.6/5.0

Behavior4/5

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

Annotations already establish that this is a read-only, idempotent, non-destructive lookup with no open-world behavior. The description adds useful behavioral context beyond that: it explains the calculation model, lists the data fields returned, and explicitly excludes welcome bonuses and credits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, but it is a single long, run-on sentence with awkward layering of calculation details, returned fields, and page/calculator references. The category list also duplicates the schema enum, which adds length without much new meaning.

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 two-parameter read-only ranking tool with no output schema, the description is sufficiently complete: it explains what is ranked, how the metric is computed, what data is included, and what is excluded. The main omissions are explicit limit behavior and clearer routing against alternatives.

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?

The schema already defines the category enum and documents the optional limit parameter with its default and maximum. The description restates the category choices in prose but does not clarify how limit affects the ranking or compensate for the missing category schema description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies a specific resource: Points Frog's ranking of popular US rewards cards for one spending category. It also explains that the ranking is based on cents back per dollar and includes issuer terms data. The purpose is clear, though the opening is a noun phrase rather than a direct verb and the sentence is dense.

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 gives the allowable spending categories and says welcome bonuses and credits are excluded, which implies when the tool is appropriate. However, it does not explicitly contrast this tool with alternatives such as the calculator or other comparison tools, and it gives no when-not-to-use guidance.

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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