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saurabhherwadkar

MCP Python Server & Client

string_operation

Perform string manipulations including reverse, case conversion, word/character counting, replacement, and truncation by specifying an operation and text.

Instructions

Perform a string manipulation operation.

Args: operation: The string operation (reverse, count_words, uppercase, lowercase, title_case, count_chars, replace, truncate) text: The input text to operate on extra: Extra parameter (replacement text for 'replace', or max length for 'truncate')

Returns: The operation result as a string

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
extraNo
operationYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the burden. It mentions the return type (string) but does not disclose any behavioral traits like side effects, state changes, or error handling. As a pure string manipulation function, it is safe, but transparency 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.

Conciseness4/5

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

The description is structured as a docstring with Args and Returns sections, making it easy to parse. It is front-loaded with the purpose. Slightly verbose for the simple nature of the tool, but acceptable.

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?

Given no annotations and no schema descriptions, the description covers the purpose, all parameters, and return value. It is fairly complete for a pure function tool. Missing context: behavior with invalid operations and potential errors.

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 description coverage is 0%, so the description must compensate. It explains the 'operation' parameter with enumerated values, 'text' as input, and 'extra' with usage for replace (replacement text) and truncate (max length). This adds significant meaning beyond the schema. However, it could clarify that 'extra' is ignored for other operations.

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 it performs string manipulation operations and lists specific operations like reverse, count_words, etc. It is a specific verb+resource that distinguishes from sibling tools (calculate, get_weather) which are unrelated.

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 lists available operations and explains parameters, providing implied usage context. However, it does not explicitly state when to use this tool vs alternatives or provide conditions for use.

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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