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IA-QA — 152 QA & Dev Tools for AI Agents

hash_text

Read-onlyIdempotent

Compute a cryptographic hash of a text string. Use when you need to verify data integrity, generate content fingerprints, hash passwords (prefer SHA-256+), or produce a fixed-length digest of any input. Supports SHA-256 (default), SHA-512, SHA-1, and MD5.

Input Schema

NameRequiredDescriptionDefault
inputYesText to hash
algorithmNoHash algorithm: sha256 (default), sha512, sha1, md5

Output Schema

NameRequiredDescriptionDefault
hashNo
algorithmNo
input_lengthNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "algorithm": "md5",
      +    "input": "héllo wörld 🌍"
      +  }
      +]
  2. Changed1 schema field changed
    • addedOutput schema / properties
      Added value: +{
      +  "algorithm": {},
      +  "hash": {},
      +  "input_length": {
      +    "type": "number"
      +  }
      +}
  3. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "additionalProperties": true,
      +  "type": "object"
      +}
  4. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare the operation as read-only, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds useful context about supported algorithms and a security recommendation to prefer SHA-256+ for passwords, which goes beyond the annotations.

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?

Two sentences, front-loaded with the core operation and followed by use cases and supported algorithms. No filler or redundancy.

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

Completeness5/5

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

For a simple two-parameter utility with full schema coverage, an output schema, and comprehensive annotations, the description provides all the context an agent needs to call it correctly.

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 coverage is 100% and the schema already documents both the input and the algorithm parameter with its default and options. The description mostly repeats the algorithm list; its only added semantic value is the password recommendation for SHA-256+.

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 and resource: 'Compute a cryptographic hash of a text string.' This is unambiguous and distinct from sibling utilities like base64_encode or generate_uuid.

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

Usage Guidelines4/5

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

Provides clear usage contexts: integrity verification, content fingerprints, password hashing, and fixed-length digests. It does not give explicit when-not-to-use or point to sibling tools, but the domain is narrow enough that alternatives are largely unnecessary.

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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