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devtools_enable_argocd

Stand up an ArgoCD instance with OpenStack health checks by setting confirm to true. Modifies the cluster, requiring GitOps operator already installed.

Instructions

Enable an ArgoCD instance with OpenStack health checks.

TOOL_NAME=devtools_enable_argocd DISPLAY_NAME=Enable ArgoCD Instance USECASE=Stand up the ArgoCD instance. Modifies the cluster. INPUT_DESCRIPTION=confirm (bool) — must be true OUTPUT_DESCRIPTION=status, stdout, stderr, exit_code EXAMPLES=devtools_enable_argocd(confirm=True) PREREQUISITES=GitOps operator installed RELATED_TOOLS=devtools_install_gitops_operator, devtools_configure_openshift_gitops

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confirmNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

There are no annotations, so the description carries the full behavioral burden. It discloses that this tool modifies the cluster and that confirm must be true, which are important guardrails. However, it does not describe reversibility, permissions, idempotency, or what specifically changes in the cluster beyond 'stand up.'

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

Conciseness4/5

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

The description is front-loaded with the core purpose and then organized into labeled metadata fields. There is some redundancy in repeated tool/display names, but the structure is scannable and each field adds practical context: use case, input, output, examples, prerequisites, and related tools.

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?

For a tool with one boolean parameter, no annotations, and an output schema, the description covers the prerequisites, the confirmation requirement, examples, and related tools. It is sufficiently complete, with the main gap being more explicit side-effect details, which are already partially covered by the 'modifies the cluster' note.

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 input schema only provides a boolean with default false and no description, while the description adds 'confirm (bool) — must be true.' This is valuable beyond the schema because it tells the agent not to rely on the default and to set the flag for the operation to proceed.

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?

The description states a concrete action—enable/stand up an ArgoCD instance—and adds a distinguishing detail: 'with OpenStack health checks.' This separates it from siblings like install_gitops_operator and configure_openshift_gitops, which target different resources or phases.

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 metadata gives a clear prerequisite ('GitOps operator installed') and lists related tools that represent the surrounding workflow. It does not explicitly say 'use this only after installing the operator and not for configuration,' but the relationships and prerequisite are clear.

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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