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by dev.agentbits

base64_encode

Convert a UTF-8 string into standard Base64 when you need a portable text encoding for credentials, binary-safe transport, or embedding data in JSON/HTTP fields.

Use when:

  • Encode this UTF-8 string as Base64

  • Convert plain text into standard Base64 for transport

  • Produce a Base64 representation of a credential or payload string

Do not use when:

  • Decode Base64 back to text (use base64_decode)

  • Percent-encode URL components (use url_encode)

  • Hash or encrypt data for security—Base64 is encoding only

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYesText to encode

TDQS

A4.6/5.0
Behavior4/5

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

Without annotations, the description carries the full burden. It discloses that Base64 is encoding-only, not for hashing/encryption, and explains use cases for credentials and binary-safe transport. It doesn't cover edge cases, but for a pure encode tool, this is adequate.

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?

The description is well-structured but the 'Use when' list contains three near-identical bullets, making it slightly redundant. Still, it's compact and front-loaded with the main purpose.

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 utility, the description covers purpose, usage scenarios, and explicitly excludes related tools. No output schema is needed for this simple tool.

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 covers the only parameter 'value' with 'Text to encode'. The description adds the UTF-8 encoding context, clarifying the expected input format. This adds semantic value beyond the schema.

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 'Convert a UTF-8 string into standard Base64', which is a specific verb+resource. It distinguishes itself from siblings like base64_decode and url_encode by explicitly naming them in the 'Do not use when' section.

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?

Provides a 'Use when' and 'Do not use when' list, explicitly naming base64_decode and url_encode as alternatives. This directly answers when to use vs alternatives.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct data format and operation, with explicit 'Do not use when' cross-references to prevent confusion. For example, base64_encode/decode, url_encode/decode, and timestamp_convert/timezone_convert are clearly separated, and the various validators (ISBN, Luhn, UUID, JSON) apply to different identifiers.

Naming Consistency4/5

Most tool names follow an object_operation pattern (e.g., base64_decode, country_lookup, timestamp_convert), using lowercase with underscores. The main deviation is countries_bulk, which uses a noun+adjective form without an explicit operation, making it inconsistent with the verb-like operations used elsewhere.

Tool Count3/5

With 18 tools, the server falls into the 16-25 range which feels heavy for a utility collection. While each tool is individually useful and the scope is broad, the count is higher than typical for a well-focused server and may overwhelm agents scanning the available options.

Completeness4/5

The set provides solid coverage of encoding/decoding, validation, lookups, and conversions, with paired encode/decode and convert functions. However, some common utilities such as hashing, HTML entity encoding, UUID generation, or email validation are absent, leaving minor gaps for agents that need those operations.

Resources