Get Conversation

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

The annotations only include openWorldHint: true, which is a minimal signal. The description goes beyond this by disclosing that looking up by username involves click-visiting matching rows and 'may mark it as read.' It also explains why this is necessary (no hrefs in LinkedIn's sidebar). This is a significant behavioral disclosure that the annotation alone does not provide.

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 for the complexity of the tool. It is front-loaded with the core purpose, then explains the two lookup paths and their trade-offs. Every sentence earns its place, and the structure is logical and easy to follow.

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?

The description fully covers the tool's behavior given its complexity: both lookup methods, side effects, and the alternative search tool. It has an output schema, so return values need not be described. The only minor omission is the lack of an explicit conflict rule when both parameters are provided, but the phrase 'Provide either' implies exclusivity and the schema does not list both as required.

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 coverage is 100%, so the baseline is 3. The description adds value beyond the schema by explaining the resolution process for linkedin_username and clarifying that index is a selector when multiple threads exist, tied to the username lookup. It also connects thread_id and linkedin_username as alternative identifiers, which goes beyond the individual parameter 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 clearly states the tool's function: 'Read a specific messaging conversation.' It distinguishes itself from siblings by specifying the two lookup methods (linkedin_username or thread_id) and by differentiating from search_conversations, which is for enumerating thread IDs. The verb 'read' and the resource 'specific messaging conversation' are concrete and unambiguous.

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 gives explicit usage guidance: provide either linkedin_username or thread_id. It names the alternative tool for enumerating thread IDs ('To enumerate thread IDs first, call search_conversations') and advises using thread_id directly to avoid the side-effect-prone username lookup. This clearly tells the agent when to use this tool and when to use a sibling.

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