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encode_base32

Encode text into Base32 or decode Base32 back to text using a compact alphabet of A-Z and 2-7, ideal for human-readable tokens.

Instructions

Encode or decode text using Base32 encoding.

Use this for compact, case-insensitive encoding suitable for
human-readable tokens, similar to Base64 but using only A-Z and 2-7.

Parameters:
    text — The string to encode or decode (required).
    mode — "encode" (text → Base32, default) or "decode" (Base32 → text).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
modeNoencode

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. It states the tool encodes/decodes and mentions the default mode, but does not disclose error handling, padding behavior, or return format. The output schema likely covers return structure, but behavioral details are minimal.

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?

The description is short and front-loaded with purpose. Every sentence contributes value: purpose, use case, and parameter details. No fluff or redundancy.

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?

Given the tool's simplicity and the presence of an output schema, the description covers essential aspects: purpose, parameters, and typical use. Minor omission: no mention of input validation or case sensitivity.

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 0%, so the description must compensate. It explains both parameters: text (required string) and mode (defaults to 'encode', with values 'encode' or 'decode'). This adds meaning beyond the schema's bare titles.

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 description clearly states that the tool encodes or decodes text using Base32 encoding, with a specific verb and resource. It distinguishes itself from sibling tools like encode_base64 by noting it uses only A-Z and 2-7, making it suitable for human-readable tokens.

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?

The description provides context for when to use Base32 encoding (compact, case-insensitive, human-readable) and compares it to Base64. However, it does not explicitly mention when not to use it or list alternative encoding schemes like Base32hex.

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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