Skip to main content
Glama

test_agent_runtime_config

Resolve configured agent runtime settings in a dry-run mode to validate configuration without writing code or connectors.

Instructions

Dry-run resolve the configured agent runtime without code or connector writes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNo
agent_typeNocoding

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. Addedv0.1.1

TDQS

B3.3/5.0
Behavior4/5

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

The description explicitly states 'without code or connector writes,' which clearly discloses that this tool is non-mutating. Since no annotations are provided, this is valuable transparency, though it does not mention other possible side effects, errors, or what 'resolve' entails beyond being a dry run.

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?

The description is a single concise sentence that front-loads the dry-run nature and the key side-effect constraint. There is no redundant or irrelevant content.

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?

The description covers the core behavior and the absence of writes, which is important context, but it leaves parameter semantics and the exact meaning of 'resolve' under-specified. Since an output schema exists, return-value details are not strictly required, but some parameter guidance would make the description more complete.

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?

The input schema has two parameters with no descriptions, and the description does not explain message or agent_type. 'agent_type' is somewhat inferable from the agent-runtime context, but 'message' remains ambiguous, so the description adds minimal meaning beyond the bare parameter names.

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?

The description identifies a specific action: dry-run resolve the configured agent runtime, and it clearly scopes the operation as one with no code or connector writes. 'Resolve' is somewhat vague, but the dry-run framing and tool name make the intent mostly clear.

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

Usage Guidelines2/5

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

The description communicates that this is a safe dry-run operation, but it gives no explicit guidance on when to use this tool over related siblings such as get_agent_runtime_config, configure_coding_agent_runtime, or list_agent_runtime_options. There is no workflow context or alternative-selection guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/RPasquale/lightbulb-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server