Check a research task's status by ID and collect its result when finished.
Poll for research task status and result. Call until status is 'succeeded' or 'failed'.
| Name | Required | Description | Default |
|---|---|---|---|
| task_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.3.1Input schema / additionalPropertiesRemoved value: -falseInput schema / descriptionRemoved value: -"Input for retrieving a browsing or research task result."Input schema / properties / task_id / descriptionRemoved value: -"The task's unique identifier"Input schema / titlePrevious value: -"TaskIdInput"New value: +"get_research_task_resultArguments"Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "result": {
+ "title": "Result",
+ "type": "string"
+ }
+ },
+ "required": [
+ "result"
+ ],
+ "title": "get_research_task_resultOutput",
+ "type": "object"
+}v0.3.0Input schema / additionalPropertiesAdded value: +falsev0.2.9Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the polling behavior and the final statuses, which complements the readOnlyHint annotation. It does not cover error handling or rate limits, but it adds useful behavioral context beyond the annotation.
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 extremely concise with two sentences, front-loading the purpose and then providing the usage instruction. Every part is relevant and efficient.
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 tool is simple with one parameter and an output schema, so the description's polling pattern and termination condition are sufficient. It lacks details on possible initial statuses or errors, but the output schema likely covers return values.
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 description does not elaborate on the only parameter 'task_id', despite the schema having 0% description coverage. The parameter's purpose is implied but not explicitly clarified, which is insufficient for complete understanding.
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 polls for the status and result of a research task, specifying the verb 'poll for' and the resource 'research task status and result'. It distinguishes from siblings like run_research_task and list_research_tasks by focusing on retrieving results.
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 explicitly instructs to 'Call until status is 'succeeded' or 'failed'', providing a clear usage pattern. It implies a polling loop but does not mention when not to use it or alternative tools, leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.