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xxHash32

checksum-xxh32
Read-onlyIdempotent

Calcula el xxHash32 con semilla opcional. Hash no criptográfico muy rápido. Cuándo: se necesita un checksum rápido no criptográfico para detectar errores, repartir datos o tablas hash. No para: calcular el MurmurHash3 x86_32 con semilla opcional (checksum-murmur3-32). Efectos secundarios: ninguno (solo lectura, sin red, sin estado guardado). Determinista: la misma entrada da la misma salida. Límites: entrada JSON de hasta 64 KB, 1 s por llamada, resultado de hasta 1 MB.

EN: Computes the xxHash32 with optional 32-bit seed. Very fast non-cryptographic hash. When: a fast non-cryptographic checksum is needed for error detection, sharding or hash tables. Not for: computing the MurmurHash3 x86_32 with optional 32-bit seed (checksum-murmur3-32). Side effects: none (read-only, no network access, no stored state). Deterministic: the same input gives the same output. Limits: JSON input up to 64 KB, 1 s per call, result up to 1 MB.

Input Schema

NameRequiredDescriptionDefault
dataYesInput data (string; required).
seedNo32-bit unsigned seed (integer; optional; default 0; min 0; max 4294967295).
input_encodingNoHow `data` is encoded (optional; one of: utf8, hex, base64; default "utf8").utf8

Output Schema

NameRequiredDescriptionDefault
hexNo
seedNo
algorithmNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / data / examples
      Added value: +[
      +  ""
      +]
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-openWorld/non-destructive, and the description adds value beyond them: determinism guarantee, no network or stored state, and concrete operational limits (64 KB JSON input, 1 s per call, 1 MB result). Those limits are exactly the kind of constraint an agent needs before calling and are not present in 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.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The content is front-loaded and well ordered (what → when → not-for → effects → limits), but the entire block is duplicated verbatim in Spanish and English, roughly doubling length with zero added information.

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?

An output schema exists, so return values need not be explained, and limits/determinism are covered. The one wrinkle is that the stated 'JSON input up to 64 KB' does not obviously square with the schema's `data.maxLength` of 1048576, which could confuse an agent working near the boundary.

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%, so the schema already documents `data`, `seed` (32-bit unsigned, default 0) and the `input_encoding` enum. The description only restates 'optional 32-bit seed' and adds no format or interaction detail beyond the schema, so the baseline 3 applies.

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+resource ('Computes the xxHash32 with optional 32-bit seed') and immediately qualifies the algorithm family ('non-cryptographic hash'), which separates it from the hash-sha*/hash-blake* siblings as well as from checksum-murmur3-32, which it names explicitly.

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

Usage Guidelines5/5

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

Explicit 'When' clause gives three concrete use cases (error detection, sharding, hash tables) and an explicit 'Not for' clause that names the alternative tool (checksum-murmur3-32) and its distinguishing trait (MurmurHash3 x86_32). Nothing about tool selection is left 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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