Takes two names (a, b) and returns the FRIENDS letter-count friendship percentage, with the letter counts and the adding trail. Example input: {"a":"Rahul","b":"Priya"}
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First person's name in Latin letters (A to Z), for example Rahul | |
| b | Yes | Second person's name in Latin letters (A to Z), for example Rahul |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It usefully discloses that the tool returns a percentage plus letter counts and an adding trail, but it does not explicitly state that the operation is stateless, what happens with invalid input, or whether errors are returned for non-Latin characters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose and followed by a compact example. Every sentence adds useful information without repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 must explain return values, and it does so by naming the friendship percentage, letter counts, and adding trail. It is nearly complete for a simple computation tool, though it omits edge-case or error behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the input schema already documents that a and b are required name strings with examples and a Latin-letter constraint. The description's example adds a concrete usage pattern but does not contribute meaningfully beyond the schema's parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action: it takes two names (a, b) and returns a FRIENDS letter-count friendship percentage, including the letter counts and adding trail. This is a clear verb-and-resource statement, but it does not explicitly distinguish the tool from its siblings flames and loveScore.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus the clearly related siblings flames and loveScore. It provides an example input but does not state conditions, exclusions, or alternative tools.
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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