research_import

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

With no annotations, the description carries the full burden of behavioral disclosure. It does this well by explaining timeout tolerance ('reconciles what committed'), idempotency (duplicate URLs skipped as 'already_present'), the allow_duplicate re-add behavior, and the cited_only fallback. This goes beyond a simple 'import' statement.

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 compact yet information-dense. It front-loads the purpose in the first sentence, then organizes behavior into short paragraphs with clear inline code references. Every sentence adds useful context without unnecessary fluff.

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 complexity (6 params, no annotations) and the presence of an output schema, the description is quite complete. It covers key behaviors, parameter origins, and edge-case handling. It could briefly mention error scenarios or what happens with invalid IDs, but the overall picture is solid.

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?

The schema has 0% description coverage, so the description must explain all parameters. It covers every parameter: notebook (name or ID), poll_task_id (source from research_start/research_status), task_id (deprecated alias), allow_duplicate (re-adds duplicates), cited_only (report-cited filtering with fallback), and max_sources (caps count). This is strong compensation for the lack of schema descriptions, though a bit more detail on max_sources and notebook resolution could push it higher.

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 opens with a clear, specific verb+resource: 'Import a completed research task's sources into the notebook.' It distinguishes this from sibling tools like research_start, research_status, and source_add by focusing on the import action and identifying the source of the poll_task_id.

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 states when to use the tool: after a research task is completed, using the poll_task_id from research_start/research_status. It also clarifies that task_id is deprecated. It does not explicitly list alternatives, but the context of importing research results makes the use case clear enough.

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