BoteX

by kubainter

Overview Schema Source Related Servers Discussions Admin

Python

Hybrid

get_task_status

Return status and result for a task started with start_task.

Instructions

Return status and result for a task started with start_task.

`status` is the task lifecycle (QUEUED | RUNNING | DONE | FAILED |
CANCELLED) — DONE here means "finished", not "succeeded"; check
`result_data.status` / `result_data.ok` for the engine outcome.
`result` is the pretty-text report; `result_data` is the structured
engine result (status, failure_kind, ok, files_touched, exec_ran,
rollback_verified, attempts[], cost_usd, ...).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`task_id`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 25, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations, the description carries the full burden, and it delivers real behavioral insight: it warns that lifecycle DONE means 'finished' not 'succeeded' and points to result_data.status/result_data.ok for the true outcome, plus enumerates the structured fields returned. It omits operational traits like auth requirements, rate limits, or whether calling on a still-running task is cheap, keeping it short of a 5.

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

Conciseness5/5

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

Front-loaded one-line purpose followed by tightly scoped clarifying notes, each of which resolves a genuine ambiguity (lifecycle vs. engine status, pretty-text vs. structured result). No filler sentences.

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

Completeness4/5

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

An output schema exists, so the description is not obligated to explain return values, yet its clarification of status vs. result_data.status prevents a real misread of the response. It is complete for invocation; only polling/lifecycle operational guidance is absent.

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?

One parameter at 0% schema coverage, so the description must compensate; it implies task_id is the identifier from start_task but never states the expected format or provenance explicitly. That gives the agent enough to map the argument, but not full semantic detail, so a 3 is fair.

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+resource ('Return status and result for a task') and immediately anchors it to the sibling tool that produces the input ('started with start_task'), which cleanly separates it from start_task and the other siblings. An agent can tell exactly what this retrieves without opening the schema.

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?

The prerequisite is explicit: this is for a task 'started with start_task', which gives the agent the correct entry condition. It stops short of stating when-not to use it (e.g., polling cadence, terminal-state behavior, or what to do instead of repeated calls), so it is clear context without full routing guidance.

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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