Load a past conversation

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

With no annotations, the description must disclose all behavioral traits. It explains the output format and context usage, but it omits important details about parameters like max_messages, include_tools, and include_reasoning, as well as any side effects, permissions, or rate limits.

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 three sentences, front-loaded with the core purpose, followed by guidance on output usage and format options. Every sentence adds value without redundancy.

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?

Given the tool has 6 parameters, no annotations, and no output schema, the description covers the main purpose and format guidance but does not elaborate on the behavior of parameters like max_messages, include_tools, and include_reasoning, leaving gaps in completeness.

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 description coverage is 100%, so baseline is 3. The description adds value for the 'format' parameter by explaining use cases for 'summary' and 'json', but it does not enhance meaning for the other five parameters beyond the schema.

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 loads a past conversation by source and id as a readable Markdown transcript, with the specific purpose of continuing it. The verb 'Load' and resource 'past conversation' are precise, and the tool's function is distinct from siblings like list_conversations or search_conversations.

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 provides guidance on when to use different format options (summary for compact handoffs, json for structured models), but it does not explicitly contrast with sibling tools or state when not to use this tool versus alternatives like summarize_conversation.

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