eliza_get_final

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

With no annotations, the description carries the behavioral burden. 'Get' implies a read-only retrieval, but it does not state whether the call changes state, requires permissions, or has side effects. For a simple getter this is minimally adequate, but richer behavioral context is absent.

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?

A single sentence with no wasted words, front-loading the verb and resource before the timing context. It is appropriately sized for a trivial getter.

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?

Given the tool's simplicity (zero parameters, no output schema, no annotations), the description covers purpose and timing sufficiently. It could state the return format more explicitly, but the low complexity means little is missing.

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?

The tool has zero parameters and the schema description coverage is 100%, so there is nothing for the description to clarify. Per the rubric, zero params yields a baseline of 4.

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 uses a specific verb 'Get' and resource 'ELIZA's farewell message,' and scopes it to 'when ending the conversation.' It implicitly distinguishes from siblings like eliza_get_initial (initial greeting) and eliza_chat, but does not explicitly name an alternative. This is clear, though not maximally differentiated.

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?

States the trigger context ('when ending the conversation'), which tells the agent when to call it. It does not mention alternatives such as eliza_get_initial or eliza_reset, nor when not to use it. So it provides clear context but no explicit alternatives.

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