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Glama

render_estimate

Estimate render time, GPU seconds, queue wait, quota and size fit before starting a Blender job, using scene history to predict wall-clock duration without consuming GPU time.

Instructions

Estimate how long a render will take BEFORE starting it (no GPU time used): GPU seconds, queue wait, wall-clock time as a human-readable string ('about 3 minutes'), and whether it fits today's free quota and the size limits. kind is 'final' (frame_start..frame_end at width x height, samples) or 'preview' (frames like '1-24'). Pass scene_id when you have one: the estimate then uses this scene's own measured render times. Tell the user the result before calling render_final.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNofinal
widthNo
framesNo
heightNo
samplesNo
scene_idNo
frame_endNo
frame_startNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does most of it: it discloses that no GPU time is consumed, that scene_id switches to measured per-scene timings, and what the result contains (GPU seconds, queue wait, quota fit, size limits). It does not state error behavior or whether results can be cached/reused, so it falls just short of full disclosure.

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?

Front-loaded with the core purpose and cost, then structured by parameter and workflow. Dense but every clause carries information; only the parenthetical rendering example ('about 3 minutes') is decorative padding.

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?

For an 8-parameter, zero-coverage, no-annotation tool this is complete: purpose, cost, parameter semantics, and the workflow step that must precede render_final are all covered. Return values are partly described even though an output schema already exists.

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 coverage is 0% and all 8 parameters are undocumented in the schema, so the description must compensate — and it does. It defines kind ('final' vs 'preview'), the frames syntax ('1-24'), the frame_start..frame_end range, width x height, samples, and the effect of passing scene_id.

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?

States a specific verb (estimate) and resource (render) with an explicit scope constraint: it runs BEFORE the render starts and consumes no GPU time. This cleanly distinguishes it from render_final and render_preview, which actually produce output.

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 use it (before starting a render), what it costs (no GPU time), and names the sibling that follows it: 'Tell the user the result before calling render_final.' It also gives a condition for the optional scene_id parameter. Routing to the alternative is unambiguous.

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