spam_conversation

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

With no annotations available, the description carries the full burden of behavioral disclosure. It implies a state-changing mutation but does not explain side effects (e.g., removal from inbox), reversibility, permission requirements, or any other consequences. This is sparse disclosure.

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 a single sentence with no wasted words, effectively front-loaded. It is concise and direct, though it could be richer in content without becoming verbose.

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?

Despite having an output schema, the description lacks essential context: no usage guidelines, no parameter semantics, and no behavioral side effects. For a mutation tool with no annotations, this is insufficient to give an agent complete confidence in when and how to invoke it.

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 0%, and the description does not mention either parameter. The names conversation_id and api_token are self-explanatory to some extent, but no additional meaning is added, and the description fails to compensate for the lack of schema documentation.

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 clear verb 'mark' and resource 'conversation' with target 'as spam', making the action unambiguous. It does not explicitly distinguish from siblings like ignore_conversation or trash_conversation, but the core purpose is clear.

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?

No guidance is provided on when to use this tool versus alternatives such as ignore_conversation or trash_conversation. There are no prerequisites, exclusions, or contextual cues, leaving tool selection entirely to the agent.

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