Retrieves the Lorentz hierarchy subsumption tree from a specified root node and returns it as JSON within a chosen collection.
Retrieve the Lorentz hierarchy subsumption tree starting from a given root_id; returns the tree as JSON in the given collection.
| Name | Required | Description | Default |
|---|---|---|---|
| root_id | Yes | The root node ID of the subsumption tree. | |
| max_depth | No | Maximum hierarchy depth. | |
| collection | Yes | The collection name. |
Changes observed during successful MCP inspections.
v4.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses that the operation retrieves data and returns a tree as JSON, implying a read-only operation, but does not cover edge cases, permissions, missing roots, or how max_depth affects the returned tree.
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?
The description is a single compact sentence with the action and scope front-loaded. Every clause contributes to identifying the operation and return format, with no filler.
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?
The tool has moderate complexity, no annotations, and no output schema. The description states the return is JSON but does not describe the tree node structure or depth behavior, leaving some contextual gaps for an agent to infer.
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 coverage is 100%, so parameter meanings are already documented in the schema. The description mentions root_id and collection, adding minor contextual framing, but does not explain max_depth or traversal semantics beyond what the schema provides.
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 uses a specific verb ('Retrieve') and resource ('Lorentz hierarchy subsumption tree'), with clear scope from a given root_id in a collection. It does not explicitly distinguish itself from sibling tools such as hyperspace_graph_traverse or hyperspace_get_concept_parents, but the resource is precise enough to identify the operation.
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?
The description states what the tool does but gives no guidance on when to use it versus alternatives. There are no exclusions, prerequisites, or comparative hints for choosing this tool over graph_traverse, get_neighbors, or get_concept_parents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.