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AiBadgr

Badgr — GPU Compute for AI Agents Copy

Official
by AiBadgr

check_launch_task

Check the status, cost, verification output, receipt, and recent log lines of a launched agent task to track progress and confirm results.

Instructions

Check an agent task started with launch_agent_task: status, cost so far, verification output, receipt and recent log lines.

Input Schema

NameRequiredDescriptionDefault
job_idYesjob_id returned by launch_agent_task
log_linesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it partially meets it by naming the returned fields (status, cost so far, verification output, receipt, logs). It does not say whether the call is a safe read, whether it polls or blocks, whether cost is cumulative, or how log output is bounded — gaps that matter for a monitoring tool with no annotations and no output schema.

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?

A single front-loaded sentence with a colon-delimited list of return contents; every clause adds information and nothing is padded.

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

Completeness3/5

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

Adequate but incomplete: it names the returned fields, which is valuable given there is no output schema, but it leaves log_lines unexplained and omits behavioral traits (read-only nature, cost semantics, log truncation) for a tool with zero annotation coverage.

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

Parameters2/5

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

Schema coverage is only 50%: job_id is documented in both schema and description, but log_lines appears nowhere in the description and has no schema description (only type/min/max/default). The description does not compensate for the undocumented parameter, which controls how much log output is returned.

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

Purpose4/5

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

States a specific verb and resource ('Check an agent task') and enumerates what it reports: status, cost, verification output, receipt, log lines. Ties it explicitly to launch_agent_task, which separates it from generic status siblings. It doesn't differentiate against check_result or badgr_status, keeping it short of a 5.

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

Usage Guidelines3/5

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

'started with launch_agent_task' gives clear implied context — use it to poll a task you launched. But there is no explicit when-not-to-use guidance and no mention of the check_result sibling that could plausibly serve a similar role, so an agent still has to infer routing.

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