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run_text_analyzer

Computes the SHA256 checksum and word statistics of supplied text, letting you verify content integrity and measure word counts in a single call.

Instructions

Calculate SHA256 checksum and word stats of a given text.

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": {
      "kwargs": "<kwargs>"
    },
    "name": "run_text_analyzer"
  }
}

Input Schema

Name	Required	Description	Default
`kwargs`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 6, 2026

TDQS

C2.7/5.0

Behavior2/5

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

With no annotations, the description carries the full disclosure burden and falls short: 'word stats' is never defined (counts? unique words? frequencies?), the return shape is unspecified with no output schema, and there is no mention of determinism, encoding, or size limits. Only the basic mutability profile (implied pure computation) can be guessed.

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 compact sentence with no wasted words and the two outputs front-loaded. Its brevity is the main cause of the information gaps, but structurally it is clean.

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

Completeness2/5

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

For a tool with an opaque 'kwargs' string parameter, no output schema, and no annotations, the description should explain input format and what the stats include. Neither is covered, leaving an agent unable to confidently construct a call or interpret results.

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

Parameters2/5

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

Schema description coverage is 0% and the single parameter is named 'kwargs' of type string, which conveys nothing about whether it expects raw text, a file path, or a serialized payload. The description says 'given text' but does not clarify how the text is supplied, so it fails to compensate for the coverage gap.

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 names two concrete operations on a specific resource: computing a SHA256 checksum and word statistics for a given text. This is a clear verb+resource statement an agent could act on. It does not differentiate from siblings, but the sibling list (findPetsByStatus, db_sample_query, exec_curl) is unrelated, so differentiation is largely moot.

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?

There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The agent must infer that this is for text hashing/word counting, which is only weakly implied by the description.

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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