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funkyfunc

coding-agents-mcp

by funkyfunc

agy_ask

Delegate a stateless question to an AI agent for immediate answers without session context. Useful for quick coding or diagnostics.

Instructions

[Legacy Alias -> delegate_ask(agent="agy")] Fast stateless inquiry with Google Antigravity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNo
promptYesInquiry or diagnostic prompt.
workspace_dirNo
timeout_secondsNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.2.0

TDQS

D1.3/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only claims 'fast stateless,' which implies no persistence but does not mention side effects, authentication requirements, rate limits, or return format. For a tool that likely invokes an external AI service, this is a significant gap.

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

Conciseness2/5

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

The description is extremely short, which is concise, but it is under-specified rather than efficiently informative. The legacy alias note is arguably metadata rather than usage guidance. It is not front-loaded with actionable information; it merely states a vague capability.

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

Completeness1/5

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

Given 4 parameters (1 required), no output schema, and no annotations, the description is grossly incomplete. It does not explain what the inquiry returns, how long it might take, or any prerequisites. An agent cannot reliably invoke this tool correctly with only this information.

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

Parameters1/5

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

Schema coverage is only 25% (only 'prompt' has a description), and the tool description adds nothing about model, workspace_dir, or timeout_seconds. It does not compensate for the undocumented parameters or explain their roles or interactions. The agent is left to guess the meaning of these fields.

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

Purpose2/5

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

The description states 'Fast stateless inquiry with Google Antigravity' but does not specify a clear verb-resource pair or what kind of inquiry (e.g., question answering, diagnostics). It only references being a legacy alias for delegate_ask, which hints at purpose but does not differentiate from siblings like agy_chat or agy_plan. It is not a tautology, but it is vague and fails to convey a concrete action.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool versus alternatives. The legacy alias note is not usage guidance. Sibling tools such as delegate_ask, agy_chat, and agy_task are not mentioned, so the agent has no basis for selecting this tool over others.

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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