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 describes what the tool retrieves (complete content including specific elements) and mentions a performance consideration (summaryOnly to conserve context), but lacks details on permissions, rate limits, error handling, or response structure. It adds some context but is incomplete for a tool with no annotation coverage.

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 and front-loaded: the first sentence clearly states the purpose, followed by a workflow tip that adds practical guidance without redundancy. Every sentence earns its place by providing actionable information, with no wasted words or unnecessary elaboration.

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's moderate complexity (retrieving conversation data with optional filtering), no annotations, and no output schema, the description is mostly complete. It covers the purpose, usage guidelines, and key parameters, but lacks details on behavioral aspects like error handling or response format. It compensates well but has minor gaps in transparency.

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 the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema: it mentions using conversation IDs from specific sources (implied in the schema) and explains the purpose of summaryOnly=true for context conservation, but doesn't provide additional syntax or format details. Baseline 3 is appropriate when the schema does the heavy lifting.

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 specific action ('Retrieves') and resource ('complete content of a specific Cursor conversation'), listing concrete components like messages, code blocks, file references, title, and AI summary. It distinguishes from siblings by specifying this tool retrieves full conversation content, unlike list_conversations (which lists IDs) or get_conversation_analytics (which provides analytics).

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 explicit guidance on when to use this tool: it specifies obtaining conversation IDs from list_conversations, search_conversations, or analytics breakdowns, and includes a 'WORKFLOW TIP' for using summaryOnly=true to conserve context. It implicitly distinguishes from siblings by not suggesting alternatives for retrieving full conversation content.

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