sample_geometry

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

No annotations are provided, so the description carries the full burden. It hints that sampling is even/random-seeded via the seed parameter, but does not state that this is a read-only, non-mutating operation, nor what the return value looks like (point positions? indices? attribute values?).

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 front-loaded sentence plus a brief Args list; nothing is bloated. The Args entries are near-useless restatements, but the structure itself is clean and appropriately sized.

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 tool with no annotations, no output schema, and 0% parameter documentation, the description is too thin: it omits return format, whether the node is evaluated/cooked, and how the seed affects determinism. An agent has enough to guess the call but not to use it confidently.

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%, so the description must compensate, but the Args block only restates parameter names tautologically ('node_path: Node path.', 'sample_count: Number of points to sample.'). It adds no format, range, or behavioral meaning beyond the schema types and defaults.

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 and resource: sampling evenly distributed points from a SOP node's geometry. This is distinguishable from siblings like sample_volume and get_points. It does not, however, explicitly contrast itself with those neighbors.

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 use this tool versus alternatives such as get_points or sample_volume, nor any preconditions (e.g. does the node need to be cooked?). The reader must infer usage from the name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.