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td_timeline_profile

Profile operator cook costs on real timeline frames to find which one drops frame rate. Forces each operator to cook per frame with GPU waited, returns job id to track results.

Instructions

What each operator costs per frame, on real timeline frames — as a job.

Reach for this when the frame rate drops and you need to know who spends the frame. Do not time cook(force=True) in td_exec: a TOP's cook only queues GPU work and returns, so a hand-written loop reads ~0 ms for a TOP that costs 80 (it took an agent a whole wrong hypothesis to see it). And do not trust td_health's cookTime alone: it is the last cook, which may be hundreds of thousands of frames old.

frames is the walk, e.g. "3000..3009"; every frame of it is measured. Every TOP/CHOP/SOP/POP at or under path (up to limit, breadth-first) is forced to cook on each frame, upstream first, and timed with the GPU waited for. Returns at once with a job id like td_timeline_run — they share one slot, since both move the timeline — and td_timeline_status shows the table so far: mean and max ms per frame, costliest first. A row marked "did not cook on its own" is what the operator would cost, not part of the frame; one marked as cooked inside an earlier measurement shares its cost with that operator (a Render TOP pulling its geometry, typically).

The timeline is paused for the walk and its play mode given back; each step forces the whole list, so a heavy network makes each step as long as its frame. Every operator cooks once more per frame than it would, so a Script operator or a network/file out runs its side effect again — profile a branch without those, or accept it. Profile a component, not /.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
limitNo
framesYes
settleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.0

TDQS

A4.8/5.0
Behavior5/5

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 discloses that the timeline is paused and play mode restored, that every operator cooks once more per frame than it would, that side effects may run again, that the tool returns a job id immediately, and that it shares a slot with td_timeline_run. It also explains the meaning of special row markers. This is rich behavioral disclosure beyond 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?

The description is long but every sentence earns its place: it front-loads the purpose, then gives exclusions, then parameter semantics, then behavioral caveats. It is dense and well-structured, though slightly verbose in the middle section about row markers.

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?

Given the tool's complexity, the lack of annotations, and the bare schema, the description is remarkably complete. It covers when to use, what it measures, how it behaves, side effects, return behavior, and related tools. The output schema exists, so return values need not be described in detail. Nothing critical is missing for an agent to invoke it correctly.

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

Parameters4/5

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. It explains `frames` as the walk (e.g. '3000..3009') and `path` as the scope with `limit` as breadth-first depth. It does not explicitly explain `settle`, but the overall parameter semantics are substantially clarified. A 4 is appropriate because most parameters are given meaningful context despite the schema being bare.

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 description states a specific verb and resource: it profiles what each operator costs per frame on real timeline frames, as a job. It clearly distinguishes itself from siblings like td_exec and td_health by explaining what it is not (not a hand-written cook loop, not last-cook time).

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?

Explicitly says when to reach for it ('when the frame rate drops and you need to know who spends the frame') and gives explicit exclusions: do not time cook(force=True) in td_exec, do not trust td_health's cookTime alone. It also names sibling tools td_timeline_run and td_timeline_status for related workflow.

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