aris_list_modelsLists available process and architecture models within a tenant/database, enabling AI agents to discover ARIS models for further operations.
List models in the tenant/database (process + architecture).
| Name | Required | Description | Default |
|---|---|---|---|
| params | No |
Changes observed during successful MCP inspections.
v1.3.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is fully covered elsewhere. The description's remaining contribution is that the listing spans both process and architecture models within the tenant/database scope, which is genuinely useful context but thin. It says nothing about result size, pagination, or filtering behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single tight sentence with the scope front-loaded and zero filler. It is appropriately short for a simple list tool, though the parenthetical at the end is the only place any real information is added.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless-in-practice list tool with no output schema, the description is minimally adequate. However, it leaves the opaque params object unexplained and gives no indication of result structure or volume, so an agent still lacks information needed to call it optimally.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single optional 'params' parameter is an opaque object (additionalProperties: true) with 0% schema description coverage, and the description never mentions it. With schema coverage this low, the description is expected to compensate, but it gives no hint about what the params object accepts or how it filters the listing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (List) and resource (models) and scopes it to the tenant/database, plus clarifies the model types covered (process + architecture). This distinguishes it from the ingest/set siblings, though it does not explicitly contrast with aris_get_model or the other aris_list_model_* siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use guidance or alternatives are provided. The description never says when to enumerate models versus fetching one with aris_get_model, nor when to reach for aris_list_model_objects or aris_list_model_attributes instead. Usage is only weakly implied by the verb 'List'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.