Get Conversation

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

The description discloses a side effect: 'Each visit selects the row in the LinkedIn UI and may mark it as read.' This directly contradicts the annotation readOnlyHint=true, which claims the tool performs no modifications. Per the scoring rules, a contradiction with annotations yields a score of 1, despite the description being otherwise transparent.

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 well-structured and front-loaded with the main purpose. The additional details about enumeration and click-visits are necessary for proper usage, but the paragraph is a bit dense. Every sentence earns its place, though it could be slightly more streamlined.

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 three optional params and a complex fallback mechanism, the description is thorough. It covers the enumeration fallback, the side effect of marking as read, the index selector behavior, and points to search_conversations for thread ID enumeration. It provides sufficient context even without needing to describe the output schema.

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?

Even though schema coverage is 100%, the description adds significant meaning beyond the schema. It explains the relationship between linkedin_username and thread_id, clarifies that index is ignored when thread_id is provided, and describes the enumeration behavior. This enriches all three parameters beyond their basic schema descriptions.

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 starts with 'Read a specific messaging conversation', which uses a specific verb and resource. It clearly distinguishes from sibling tools like get_inbox (list all conversations) and search_conversations (enumerate thread IDs), and explains the two identification paths.

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 explicitly states when to use the tool and how to choose between linkedin_username and thread_id. It also directs users to call search_conversations to enumerate thread IDs first, and explains when to pass thread_id directly, providing clear context and an explicit alternative.

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