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agentspan-ai

MCP Test Server

by agentspan-ai

string_split

Split a text string into parts using a specified delimiter to parse lists, CSV-style data, or tokenized input.

Instructions

Split a string by a delimiter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
delimiterYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.4

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, and it reveals nothing beyond the headline action. Edge-case behavior that matters for a splitter -- empty delimiter, empty input string, whether trailing delimiters yield empty tokens -- is not stated.

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?

A single front-loaded sentence with zero padding, appropriate for the tool's simplicity. It is efficient, though its brevity shades into under-specification rather than true conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need no explanation, and this is a trivial pure function. However, the absence of annotations and of any edge-case behavior leaves the definition only minimally complete.

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 0%, so the description must compensate for two undocumented parameters. It conceptually names both inputs (the string and the delimiter), giving a reasonable one-to-one mapping, but adds no detail on delimiter format or multi-character handling.

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 states a specific verb (split) and resource (a string) with the delimiting mechanism, which clearly separates it from the inverse sibling string_join. It stops short of explicitly naming alternatives or conditions, but the purpose is unambiguous.

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

Usage Guidelines2/5

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

No guidance on when to use this versus siblings like string_replace or string_join, and no mention of edge-case preconditions. The usage context is left entirely to inference from the name.

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