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SuZiXunYue

IDA Script MCP

by SuZiXunYue

check_task_status

Read-onlyIdempotent

Poll the status of a long-running IDAPython script task in IDA Pro after execute_idapython times out, and retrieve results once completed.

Instructions

Check the status of a long-running script execution task.

Use this tool when execute_idapython returns a task_id with status 'running' or 'pending', indicating the script is still executing in IDA Pro and the timeout was exceeded.

Args: task_id: The task ID returned by execute_idapython instance_id: Target IDA instance ID (optional, uses default if not specified) port: Target IDA instance port (optional, uses default if not specified)

Returns: str: JSON-formatted task status with result if completed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
portNo
task_idYes
instance_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful context beyond that — the task runs in IDA Pro, the status reflects a timeout-exceeded execution, and a completed task carries its result — though it gives no polling cadence or expiry guidance.

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?

Purpose and usage are front-loaded in the first two sentences, with Args/Returns sections following in a scannable layout. The Returns line slightly restates what the output schema already provides, which is the only wasted content.

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?

For a read-only polling tool with three params, the description covers the trigger condition, every parameter's origin and optionality, and the completion semantics. Return shape details are already handled by the existing output schema, so nothing an agent needs to call this correctly is missing.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must carry the parameter burden, and it does: task_id is identified as the value returned by execute_idapython, and instance_id/port are explained as optional target selectors that fall back to defaults. It stops short of describing what a non-default instance_id or port implies for routing.

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?

States a specific verb and resource ('Check the status of a long-running script execution task') and immediately names the sibling that produces the input (execute_idapython), so an agent can distinguish it from cancel_ida_task or check_ida_connection without opening a schema.

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

Usage Guidelines5/5

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

Explicitly states the triggering condition: use when execute_idapython returns a task_id with status 'running' or 'pending' because the timeout was exceeded. This is a precise when-to-use rule tied to a named sibling rather than an inferred one.

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