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decode_payload

Decode base64, base64url, hex, URL-encoded values or JWTs locally. Automatically detects the format and shows alternate decodings when input is ambiguous.

Instructions

Decode base64, base64url, hex, URL-encoding or a JWT, detecting the format when encoding is 'auto'. Ambiguous input returns every plausible decoding under alternatives rather than picking one silently. Local only: nothing is sent anywhere. Cost: free, no quota, instant.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe encoded value.
encodingNoForce an encoding, or 'auto' to detect.auto

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
decodedYes
printableNo
truncatedNo
alternativesNo
bytes_lengthNo
encoding_chainNo
detected_encodingYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries the full disclosure burden and does so well: local-only execution, nothing transmitted, no quota, instant, and the non-obvious behavior of returning every plausible decoding under 'alternatives' for ambiguous input instead of silently guessing. That ambiguity-handling detail is exactly the kind of trait an agent cannot infer elsewhere.

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?

Three compact sentences, no filler, with the core capability front-loaded and the supplementary guarantees (local, free, instant) trailing. Every clause earns its place.

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?

An output schema exists, so return-value documentation is unnecessary, and the description covers the remaining unknowns: format coverage, detection behavior, ambiguity handling, and execution guarantees. Nothing an agent needs to call this 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 description coverage is 100%, so the baseline is 3; the description goes beyond the schema by explaining what 'auto' actually does (detection) and by describing the semantic consequence of forcing vs. not forcing an encoding. It adds meaning without restating enum values verbatim.

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 (decode) plus an explicit enumeration of the formats handled (base64, base64url, hex, URL-encoding, JWT), and clarifies the 'auto' behavior. An agent can distinguish this from sibling tools like analyze_jwt or parse_url without opening any schema.

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?

Explains the condition that drives the tool's behavior ('detecting the format when encoding is auto') and the fallback for ambiguous input, giving clear context for use. It does not, however, route the agent away from close siblings such as analyze_jwt or explicitly state when this tool is the wrong choice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.