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Python
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hash_text

Generate SHA-256, SHA-512, or BLAKE2b hashes from UTF-8 text and return lowercase hex values for verification or storage.

Instructions

Hash UTF-8 text using SHA-256, SHA-512, or BLAKE2b; return lowercase hex.

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": {
      "text": "<text>"
    },
    "name": "hash_text"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYes
algorithmNosha256

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It usefully discloses input encoding (UTF-8) and output format (lowercase hex), which are genuine behavioral facts, but says nothing about determinism, empty-string handling, or error behavior for unsupported inputs. For a pure, side-effect-free function the remaining risk is low.

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?

A single tight sentence that front-loads the action and resource and ends with the output format. No filler, nothing to trim.

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?

No output schema and no annotations exist, so the description had to state the return shape, which it does ('lowercase hex'). For a two-parameter, side-effect-free utility this is nearly complete; the only gap is explicit handling of the optional algorithm default, which the schema already covers.

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. It enumerates the three algorithm values (matching the enum) and clarifies the input is UTF-8 text, but does not explain the 'text' parameter's expected content or reflect the sha256 default. Partial compensation only.

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?

States a specific verb (hash), the exact resource (UTF-8 text), the supported algorithms, and the output encoding. Among siblings like analyze_text, compare_text, and process_json, it is immediately clear this is the deterministic hashing utility.

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?

Usage is implied by the description — you use it when you need a hash digest of text — but there is no explicit when-to-use/when-not, no mention of alternatives for non-hash needs, and no prerequisites. Adequate but leaves routing to inference.

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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