research_status

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

The description discloses key behavioral traits: blocking until complete or timeout, compact truncation, auto_import behavior, and task_id/query fallback. With no annotations, these disclosures are essential and well-covered, though error behavior on timeout is not detailed.

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 structured with an 'Args:' block and each parameter has a concise explanation. While not extremely terse, every sentence adds value for a tool with 7 parameters. It could be slightly more compressed but is not verbose.

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 description covers parameters, behavior, and workflow (auto_import vs manual). An output schema exists (not shown), so return values are assumed documented. Missing details about timeout handling and error cases, but overall complete for a polling tool.

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?

All 7 parameters are explained with defaults, purpose, and behavioral implications (e.g., compact truncates, auto_import triggers import). Schema description coverage is 0%, so the description fully compensates, adding meaning beyond the raw 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 'Poll research progress. Blocks until complete or timeout.' It uses a specific verb (poll) and resource (research progress), and the sibling tool set includes research_start and research_import, making the purpose distinct.

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 implicitly indicates when to use this tool (after starting research) and provides guidance on auto_import and fallback matching via query. However, it does not explicitly compare to sibling polling tools like notebook_query_status, so evaluation is slightly less clear.

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