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cook_frame_range

Cook a node across a frame range to advance sequential solvers and report per-frame changes, errors, counts, bounds, and attributes in one call instead of looping.

Instructions

Cook a node frame by frame and report what changed on each frame.

This is how you advance a sequential solver and how you prove a simulation is doing something. Frames are cooked in order, so a SOP solver, a DOP network or an animated chain all accumulate correctly, and per-frame cook time, errors, counts, bounding box and attribute aggregates come back in ONE round trip instead of one per frame. static: true means counts and bounds never changed over the range: the node cooks but does nothing. Past 25 frames the rows are 25 evenly spaced frames plus every frame with an error or warning (frames_shown); totals, static and slowest_frame still cover every frame.

Prefer this over set_frame in a loop, and over stepping by hand: a 100-frame check is one call rather than 100. The frame is left where the cook ended, ready to screenshot.

No deadline: a heavy sim runs under Houdini's progress bar for as long as it takes; wait for the verdict and call nothing else meanwhile. Stopped from that bar, it answers interrupted: true with the frames cooked so far. A node that keeps a cache across frames (Trail, SOP Solver) starts from what it holds: press_button its reset (Trail: clear) or reset_simulation first.

Args: node_path: Node to cook; its output is what gets measured. start: First frame. Defaults to the playbar start. end: Last frame, inclusive. Defaults to the playbar end. step: Frame increment. Keep at 1.0 for any solver, since skipping frames gives it a discontinuous time step and invalid results. attribs: Point attributes to aggregate per frame (min/max/mean/sum). volumes: Also report per-volume name, resolution and value range.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
stepNo
startNo
attribsNo
volumesNo
node_pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.24.1
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

No annotations exist, so the description carries the full burden, and it does: blocking semantics with no deadline, `interrupted: true` when stopped from the progress bar, the `static: true` meaning, the 25-frame sampling rule with `frames_shown`/`slowest_frame` still covering all frames, and the final frame position after cooking. These are non-obvious traits an agent could not infer from the schema.

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

Conciseness4/5

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

It is long but front-loaded: purpose first, then behavioral caveats, then alternatives, then args. Nearly every sentence carries load-bearing information, though the density (multiple named flags and edge cases in two paragraphs) makes it slightly heavier than necessary for a single tool call.

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?

With no annotations and no output schema, the description supplies what is missing: return shape (per-frame cook time, errors, counts, bbox, attribute aggregates in one round trip), failure/interruption behavior, and inter-tool prerequisites. Nothing an agent needs in order to invoke it correctly appears absent.

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 documents all six parameters: node_path (output is what gets measured), start/end defaults from the playbar, step with the explicit 'keep at 1.0 for any solver' rationale, attribs aggregation functions (min/max/mean/sum), and volumes reporting. This goes well beyond the bare titles in the schema.

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?

The first sentence states a specific verb and resource ('cook a node frame by frame') and immediately adds the distinguishing output ('report what changed on each frame'). It explicitly contrasts itself with siblings by name (set_frame, press_button, reset_simulation), so an agent can separate it from the many cook/step tools in the sibling list.

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

Usage Guidelines5/5

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

It gives an explicit preference rule: 'Prefer this over set_frame in a loop, and over stepping by hand: a 100-frame check is one call rather than 100.' It also names the preconditions for correct use (reset Trail's `clear` or reset_simulation when a node holds a cross-frame cache) and warns against step > 1.0 for solvers.

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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