Read point positions and selected attributes from a Houdini node with pagination and group filtering.
Read point positions and attributes with pagination.
Args: node_path: Node path. attributes: Attribute names to read. start: Start index. count: Max points per page. group: Point group filter.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | ||
| group | No | ||
| start | No | ||
| node_path | Yes | ||
| attributes | 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 burden of disclosing behavior. It states the operation is a read and mentions pagination, but does not describe actual pagination semantics (e.g., default page size, how start/count interact, what happens when count is omitted), return format, or any error conditions. This leaves essential runtime behavior unspecified.
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 compact and front-loaded with the core purpose. The Args list is a clean, scannable way to convey parameter meanings without verbose prose. No wasted sentences.
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 5-parameter read tool with no annotations and no output schema, the description provides adequate parameter guidance but lacks critical context: what the returned data structure looks like, how pagination behaves at page boundaries, the role of the group filter, and any performance or ordering guarantees. This is enough for a basic call but not for confident robust usage.
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 Args block adds meaningful definitions for all five parameters beyond the bare schema titles: 'Attribute names to read,' 'Start index,' 'Max points per page,' 'Group point group filter.' This is significantly more informative than the schema alone, which only provides type/title. Node_path remains minimally described as 'Node path,' but overall the parameter semantics are well covered.
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 opens with 'Read point positions and attributes with pagination,' which clearly identifies the operation (read), the resource (points), and the key feature (pagination). It does not explicitly differentiate from sibling tools like get_prims or get_attrib_values, but the tool name and description make its scope unambiguous.
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 is provided. The description does not mention alternatives or conditions under which an agent should choose get_points over get_attrib_values, get_prims, or sample_geometry. Context must be inferred entirely from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.