Get Conversation

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

The description discloses that the tool click-visits rows and 'may mark it as read,' which indicates a side effect on state. This directly contradicts the annotation readOnlyHint: true, so the description contradicts structured metadata. Therefore, the behavioral transparency score is a 1 due to this contradiction.

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 appropriately sized and front-loaded with a clear purpose statement. All subsequent sentences provide necessary procedural or contextual information, with no wasted words. It is structured logically from identification to mechanics.

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 tool with moderate complexity, the description comprehensively covers lookup methods, behavioral side effects, parameter usage, and references to related tools. An output schema exists, so return values need no additional explanation. The only issue is the annotation contradiction, which is captured in the behavioral transparency dimension.

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?

Although schema description coverage is 100%, the tool description adds meaningful context beyond the schema. It clarifies the mutual exclusivity of linkedin_username and thread_id, explains the 'index' parameter's role in multi-thread scenarios, and provides procedural detail about the enumeration process.

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 explicitly states the tool reads a specific messaging conversation, using the verb 'Read' and resource 'messaging conversation'. It distinguishes this from siblings like search_conversations and get_inbox by focusing on retrieving a single conversation by identifier.

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 clearly instructs when to use linkedin_username versus thread_id, notes that thread_id skips the enumeration process, and references search_conversations for enumerating thread IDs. This gives explicit guidance on alternative tools and when to use each parameter.

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