research_get

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

With no annotations, the description carries the full burden. It discloses the output behavior (saves cited Markdown to output_dir, returns path) and a key requirement (pass same format/citation/tone). However, it does not describe what happens when the task is still running (e.g., returns pending status), any error conditions, or side effects beyond saving the file. It is moderately transparent but not comprehensive.

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 two sentences, front-loaded with the action ('Poll a running research task'), and every clause adds value. It avoids redundancy with the schema and is appropriately sized for the tool's complexity.

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 polling tool with 7 parameters and no output schema, the description covers the core workflow: poll, save, return path, and reuse parameters. It does not explain the output_filename parameter or the behavior before task completion, but for a straightforward polling tool the description is largely sufficient. The missing details are minor given the sibling context.

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 only 43%, but the description adds significant meaning beyond the schema by telling the agent to 'Pass the same format/citation/tone used to start it.' This links the optional parameters (format, citation_style, tone) to the originating research task, which is crucial for correct invocation. It also implies interaction_id ties to deep_research. This compensates well for the schema gaps.

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 uses a specific verb ('poll') and identifies a clear resource ('a running research task'), distinguishing it from siblings like deep_research (likely starting) and research_followup (likely follow-up). It also states the outcome (saves Markdown report and returns path), fully clarifying its role.

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 clearly indicates when to use: when a research task is already running, not to start a new one. It provides context ('Poll a running research task') and a key instruction about reusing format/citation/tone, but does not explicitly exclude alternatives or mention when not to use it. Thus it has clear context but no formal exclusions.

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