Exa MCP Server

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

With no annotations provided, the description carries the full burden and does so effectively. It discloses key behavioral traits: the built-in 5-second delay before checking, the polling requirement, and the status-based workflow ('running' vs 'completed'). It doesn't cover error handling or rate limits, but provides substantial operational context.

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 efficiently structured with zero wasted sentences. It front-loads the core purpose, then provides essential operational details (delay, polling instructions). Every sentence earns its place by conveying critical information for correct tool invocation.

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?

For a single-parameter tool with no annotations and no output schema, the description provides excellent context about the polling behavior and workflow. It could be more complete by describing the output format or error conditions, but given the tool's relative simplicity, it covers the most critical aspects well.

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 the single parameter (taskId). The description adds context by specifying that the taskId comes from deep_researcher_start, which is helpful but doesn't provide additional semantic meaning beyond what the schema indicates. This meets the baseline for high schema coverage.

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 purpose with specific verbs ('check the status', 'retrieve results') and identifies the resource ('deep research task'). It distinguishes from siblings like deep_researcher_start (which initiates research) by focusing on monitoring and result retrieval rather than task creation.

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 usage instructions: call this tool repeatedly (poll) until status becomes 'completed', and when status is 'running', wait a few seconds and call again with the same task ID. It also implicitly distinguishes from siblings by referencing deep_researcher_start as the source of the task ID.

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