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get_task_status

Read-only

Poll the status of an async job (generate_report_for_stock, generate_research_report, explore_data_catalogue, explore_data_coverage, draft_custom_dataset, screen_stocks, ...).

Returns {"task_id": ..., "status": ..., "result": ...}. `status` is one of
PENDING, SUCCESS, FAILURE, RETRY. `result` is populated once status is SUCCESS.

A result over ~8 MB is not returned (it would take the server down): the call errors.
Re-run the job scoped narrower (tickers, dates, a row limit in the wording) instead of
polling it again.

Input Schema

NameRequiredDescriptionDefault
task_idYesThe task_id an async tool returned.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Although annotations already declare readOnlyHint, the description adds substantial behavioral context beyond them: the exact status values (PENDING, SUCCESS, FAILURE, RETRY), when result is populated, and the critical >8 MB failure mode with remediation advice. This is exactly the kind of operational detail an agent needs to avoid misusing the tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose, then return shape, then a critical caveat, which is a logical structure. The parenthetical list of async job names is somewhat lengthy, but it serves to identify applicable tools and every sentence provides actionable information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, yet the description fully specifies the return object keys, status enum, result population condition, and the error behavior when results exceed ~8 MB. Nothing essential for correct invocation and result interpretation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single task_id parameter has 100% schema description coverage ('The task_id an async tool returned'), so the schema already carries the parameter meaning. The description adds return-shape context but no additional parameter syntax or constraints, making baseline 3 appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource ('Poll the status of an async job') and enumerates the sibling async generators it applies to (generate_report_for_stock, screen_stocks, etc.). An agent can immediately distinguish it from those generator tools and from synchronous data retrieval tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It clearly indicates this is for polling an async job's status, and gives explicit handling guidance for the oversized-result case ('re-run the job scoped narrower ... instead of polling it again'). It doesn't explicitly say to call this only after an async tool returns a task_id, but that is strongly implied.

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

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