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AiBadgr

Badgr — GPU Compute for AI Agents Copy

Official
by AiBadgr

badgr_status

Lists active GPU deployments for the account, letting AI agents verify running compute and monitor workload status.

Instructions

List active Badgr GPU deployments for this account.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral burden. It usefully discloses two traits: the result is filtered to 'active' deployments only, and it is scoped to the caller's account rather than all accounts. It does not say whether results are paginated, what 'active' means, or what the response looks like.

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?

One sentence, front-loaded with the verb and scope, with no filler. Every clause earns its place by narrowing the result set.

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?

For a zero-parameter read tool this is close to adequate, but with no annotations and no output schema the agent still cannot tell what a status entry contains or how to interpret 'active'. A brief note on return shape would complete it.

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?

The tool takes zero parameters, so the baseline is 4; there is nothing for the description to disambiguate. It correctly implies no filtering arguments are needed because account scope is implicit.

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 ('List') and resource ('active Badgr GPU deployments') scoped to 'this account'. An agent can distinguish it from badgr_run/badgr_down/badgr_logs by the listing intent, though it never names those siblings explicitly.

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?

Usage is only implied: an agent can infer this is the discovery/status check before or after run/down/serve, but the description gives no explicit when-to-use or when-not-to-use guidance and names no alternative.

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