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

Annotations already mark it read-only, idempotent, and non-destructive. The description adds valuable behavioral context: UTF-8 safety for accents and emoji, and a clear error return. These details go beyond the annotations and help an agent anticipate edge cases.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is two short sentences plus a source URL. It is front-loaded with the core action and includes only essential details. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter tool with rich annotations and full schema coverage, the description covers all necessary behavior: what it does, UTF-8 safety, return type, and error handling. The provided schema and annotations fill any remaining gaps.

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

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

Schema description coverage is 100%, so the parameters are already well documented. The description adds minimal extra meaning, mostly reinforcing that 'text' is the content to convert. It does not introduce any new parameter-level insight beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with specific verbs: 'Encode text to Base64, or decode a Base64 string back to text.' It names the exact resource (Base64) and distinguishes from similar tools like base32_encoder. No ambiguity.

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

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

The description makes the usage context obvious: use it when you need Base64 encoding or decoding. The dual-mode nature is explicitly stated. It does not mention alternatives, but for a standard encoding tool the context is clear enough.

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