get_conversation

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It conveys that the tool retrieves history (read operation) and returns ordered messages, but lacks details on error handling, rate limits, or what happens if the partner does not exist.

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 extremely concise, consisting of three short sentences that each add essential information: what the tool does, what it returns, and when to use it. No unnecessary words or repetition.

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?

While an output schema exists (so return format is covered elsewhere), the description does not explain parameter usage or pagination (limit, before_id). Given the tool has 3 parameters and sibling tools for similar tasks, the description is minimally adequate but leaves gaps in conceptual understanding.

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 input schema has 3 parameters with 0% description coverage, yet the description adds no information about any parameter meanings or usage. The parameters limit, before_id, and partner_bot_id are left entirely undocumented in the description, requiring the agent to infer their purpose from the tool's name and schema defaults.

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 'Fetch' and clearly identifies the resource 'recent message history between this agent and one partner'. It also describes the return format as ordered list with reply_text inline, distinguishing it from sibling tools like list_conversations which list conversations rather than messages.

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: 'Use to give the LLM conversational context before composing a reply.' This provides clear context for usage, though it does not mention any exclusions or alternative tools.

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