Retrieve standing preference facets (user, project, effective) and catalog defaults for every HyperRoute route; optionally scope to a project and identify compliance constraints worth storing.
The standing facet layer applied to every route (user, project, effective), plus catalog:
every facet with defaults; constraint: true marks compliance checks worth storing.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses returned layers (user, project, effective), catalog defaults, and a constraint marker, which adds useful read-return context, but it does not explicitly state read-only behavior or explain scoping/auth implications.
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?
It is a single dense sentence with little waste, but it is not front-loaded with the tool's purpose. The jargon-heavy structure makes the definition harder to parse than needed.
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?
There is no output schema and the only parameter is undocumented, so the description needs to do more. It hints at return categories but leaves the project_id behavior and exact preference structure unclear.
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?
Schema description coverage is 0% and the only parameter, project_id, is never explained in the description. The mention of a 'project' layer hints at project scope, but it does not clarify whether project_id is optional or what it filters.
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?
The description never states a clear verb or plainly says it retrieves preferences. It describes an internal 'facet layer' and catalog structure, so the tool's actual purpose is only inferable from the name and sibling set_preferences.
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?
There is no guidance on when to call get_preferences versus set_preferences or other siblings. It implies a read of standing preferences but does not specify context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.