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 explicitly reveals that long messages are clipped and explains how to override this (raise max_message_chars), which is a key behavioral trait. It implies a read-only operation but doesn't state side effects or permissions; however, the clipping detail adds valuable context beyond the schema.

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?

Two sentences with zero waste. The first sentence states the purpose immediately; the second adds a behavioral note and a direct actionable hint. The structure is front-loaded and every word earns its place.

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 tool is simple and has an output schema (which presumably defines the return structure), so the description doesn't need to explain return values. It covers the core function and the clipping behavior, which is the main nuance. It lacks mention of error cases (e.g., nonexistent conversation) but that's not critical for a basic read operation given the schema covers inputs and outputs.

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 all three parameters are already described in the input schema. The description adds value by explaining the practical effect of max_message_chars ('Long messages are clipped... raise it when you need full text') and ties it to the parameter, going beyond the schema's simple 'Per-message clip length' definition.

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 ('Read') with a precise resource ('one full conversation, including its messages'), making it clear this tool retrieves a single conversation by ID. It implicitly differentiates from siblings like list_conversations (which lists) and search_conversations (which searches) without confusion.

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 establishes clear context: this is the tool for reading a specific conversation's messages. It doesn't explicitly contrast with alternatives or state when not to use it, but the parameter description (conversation_id from list_conversations) and the tool name imply the scenario well. It also provides guidance on adjusting max_message_chars for full text, which indicates a specific use case.

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