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Decode base64 to text

decode-base64-to-text
Read-onlyIdempotent

Base64 to UTF-8 text. text holds standard base64: A to Z, a to z, 0 to 9, + and /, padding optional; white space is ignored. It refuses empty text, more than 1,048,576 bytes, the URL-safe alphabet, a length or padding that cannot be base64, and bytes that are not valid UTF-8. Free. The answer is the JSON envelope of https://foundry.dap.solutions/api/decode-base64-to-text, byte for byte, with the artifact hash that answered. Full rules: https://foundry.dap.solutions/hub.md

Input Schema

NameRequiredDescriptionDefault
textYesBase64 that decodes to UTF-8 text: the letters A to Z and a to z, the digits 0 to 9, + and /, then one or two = of padding at the end, which may be left out but, when given, must make the length a multiple of four. A length that leaves one character over a multiple of four is refused. White space anywhere is ignored and not counted in the length. At most 1,048,576 bytes of UTF-8, white space included.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already establish the safe/idempotent read profile, and the description goes well beyond them: the exact size ceiling, the permitted alphabet, the refusal conditions, cost ('Free'), and the return shape (the endpoint's JSON envelope with an artifact hash). That is unusually rich disclosure for a stateless converter with no output schema.

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?

Front-loaded with the transformation first, then constraints, then return shape and pointer — a sensible ordering. It is dense but the only real overhead is the repeated full URL, which could be shortened without losing meaning.

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 single-parameter, side-effect-free tool with no output schema, the description supplies the input grammar, the failure modes, the byte ceiling, and the structure of the returned envelope. Nothing an agent needs in order to call it correctly is missing.

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

Parameters4/5

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

Schema coverage is already 100%, so the baseline is 3; the description earns an extra point by adding refusal semantics not spelled out in the schema, notably that the URL-safe alphabet (- and _) is rejected. It does partly restate the schema's whitespace and padding rules, which keeps it from a 5.

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?

The first sentence names a specific verb and resource ('Base64 to UTF-8 text'), and the body constrains exactly what 'text' means. It is unmistakable against siblings like compute-day-count-to-settlement or diff-two-line-lists, none of which involve encoding.

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?

It clearly states acceptable input and enumerates the refusal cases (empty input, >1,048,576 bytes, URL-safe alphabet, impossible length/padding, invalid UTF-8), which tells an agent when this call will fail. It stops short of naming alternatives, though no sibling overlaps in purpose, so there is little ambiguity to resolve.

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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