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Aaryan-Kapoor

MCP Character Tools

Count Multiple Letters

count_letters
Read-onlyIdempotent

Count occurrences of multiple letters at once in text, with case sensitivity and position details.

Instructions

Count occurrences of multiple letters at once.

Efficiently counts several letters in a single call.

Args:

  • text (string): The text to analyze

  • letters (string[]): Array of letters to count

  • case_sensitive (boolean): Match case exactly (default: false)

Returns: Results for each letter with counts and positions.

Example: count_letters("strawberry", ["r", "s", "e"]) → r: 3, s: 1, e: 1

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe text to analyze
lettersYesLetters to count
case_sensitiveNoMatch case exactly
Behavior4/5

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

Annotations already indicate readOnly and idempotent. Description adds that it returns counts and positions, and case_sensitive defaults to false, providing behavioral context beyond annotations.

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?

Description is concise with clear sections for Args, Returns, and Example. Every sentence adds value without redundancy.

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?

With no output schema, description adequately describes return format (counts and positions). Tool complexity is low, and the description covers key aspects for an agent to use it correctly.

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

Parameters4/5

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

Schema coverage is 100%, but description adds an example showing how parameters work together and clarifies that letters are an array of single characters, adding value beyond schema.

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 tool counts multiple letters at once, using specific verb+resource. It distinguishes from sibling 'count_letter' by explicitly saying 'multiple letters' and provides an example.

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

Usage Guidelines4/5

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

The description suggests efficiency for multiple letters, implying use over single-letter calls. However, it lacks explicit when-not-to-use or alternative tool names.

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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