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get_prim_intrinsics

Read intrinsic values for one, many, or all primitives in one call instead of per-prim requests, with optional index/range filters and summary stats.

Instructions

Get intrinsic values for primitives: one, many, or all of them.

Read many prims in one call rather than one call per prim. intrinsics alone sweeps every prim for those intrinsics and answers with a prims table plus stats (min/max/avg and the prim index each extreme belongs to, per component for a vector such as bounds); prim_indices or prim_range narrow it to the prims you care about. Up to 2000 rows per call; beyond that the reply says truncated and requested_count, and stats cover only the rows returned: page with prim_range.

Args: node_path: Node path. prim_index: One primitive index, or None for a summary. prim_indices: Several primitive indices, read in one call. prim_range: [start, end] (end inclusive) instead of a list. intrinsics: Only these intrinsics, e.g. ["bounds", "packedfulltransform"]. With none of the index arguments, they are read for every prim.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
node_pathYes
intrinsicsNo
prim_indexNo
prim_rangeNo
prim_indicesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.24.1
    • addedInput schema / additionalProperties
      Added value: +false
  2. Changed3 schema fields changedv2.21.0
    • addedInput schema / properties / intrinsics
      Added value: +{
+  "anyOf": [
+    {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Intrinsics"
+}
    • addedInput schema / properties / prim_indices
      Added value: +{
+  "anyOf": [
+    {
+      "items": {
+        "type": "integer"
+      },
+      "type": "array"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Prim Indices"
+}
    • addedInput schema / properties / prim_range
      Added value: +{
+  "anyOf": [
+    {
+      "items": {
+        "type": "integer"
+      },
+      "type": "array"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Prim Range"
+}
  3. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses the 2000-row cap, the `truncated`/`requested_count` reply fields, that `stats` cover only returned rows, and the pagination workaround via `prim_range`. It also describes the return structure (a `prims` table plus per-component stats with min/max/avg and the extreme prim index).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the one-line purpose, then behavior/pagination, then a compact Args block. Dense but every sentence carries information the schema does not, so nothing is wasted despite the length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, yet the description describes the return shape, the truncation contract, and the pagination path — everything an agent needs to call it correctly and interpret the response. Nothing material is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

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, and it does: each of the five parameters is explained, including the non-obvious semantics that `prim_index: None` yields a summary, that `prim_range` is end-inclusive, and that `intrinsics` with no index argument reads every prim.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific verb+resource ('Get intrinsic values for primitives') and immediately scopes the cardinality ('one, many, or all of them'). This distinguishes it from geometry-reading siblings like get_prims, get_points, and get_geometry_info, which cover different data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a clear when-to-use directive ('Read many prims in one call rather than one call per prim') and explains which argument selects which mode (intrinsics alone sweeps every prim; prim_indices/prim_range narrow). It does not name a sibling alternative explicitly, so it falls short of a 5.

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

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