MyClaw Toolkit MCP Server

text_tools

Count characters, reverse strings, and convert text case (upper, lower, title) using simple text processing actions.

Instructions

Text processing utilities (count, reverse, case conversion)

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": {
      "action": "<action>",
      "text": "<text>"
    },
    "name": "text_tools"
  }
}

Input Schema

Name	Required	Description	Default
`action`	Yes	Operation
`text`	Yes	Text to process

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1Jun 23, 2026

TDQS

B3.1/5.0

Behavior2/5

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

No annotations are provided, so the description carries full burden. It only says 'utilities', failing to disclose safety (read vs write), idempotency, auth needs, or rate limits. While text transformations are typically safe, the description should explicitly state that it does not modify external state.

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?

Single sentence, no filler. Front-loaded with the core purpose. Every word earns its place.

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?

For a simple utility with 2 parameters and no output schema, the description is adequate. However, it lacks specification for the 'count' action (e.g., word or character count) and does not mention output format, which could cause ambiguity.

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 100%, with descriptions for both parameters ('Operation', 'Text to process'). The tool description adds a parenthetical list of operations that partially overlaps with the enum, but doesn't add deeper meaning (e.g., what 'count' counts). Baseline 3 is appropriate since schema already covers the parameters.

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?

Description clearly states it provides text processing utilities including count, reverse, and case conversion. This distinguishes it from unrelated siblings like ai_translate or base64. However, 'count' is ambiguous (characters, words?) and case conversion isn't explicitly defined as upper/lower/title without cross-referencing the schema.

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 tool versus sibling tools. Siblings include many text-related tools (ai_translate, hash, markdown_to_html), but the description offers no comparative context or prerequisites.

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