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Critique a .riv: filmstrip + onion skin + motion vectors + metrics + checklist

riv_critique

Critique Rive animations in one call: get filmstrip, onion-skin, motion vectors, metrics, and a 7-axis scoring checklist. Spot and fix motion flaws, then re-run to improve scores.

Instructions

One-call review bundle for the render→critique→revise loop. Returns (1) a FILMSTRIP image — N frames left→right across the duration, so motion is readable as a sequence, (2) an ONION-SKIN image — all frames ghost-overlaid so every mover leaves a visible trail (use it to check trajectories and travel direction vs the artwork's facing), (3) a MOTION REPORT — net displacement/rotation vector per animated object computed from the file data, (4) objective design metrics + lint findings, and (5) a fixed 7-axis scoring checklist (incl. spatial/directional coherence). LOOK at the images, score each axis 1-5, fix anything below 4 (riv_edit / regenerate), then re-run. Iterate at least twice before delivering any non-trivial scene.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesPath to the .riv file
widthNoWidth of each filmstrip cell (default 200 — keep small, it saves tokens)
framesNoFrames to sample across the duration (default 6)
artboardNo
animationNoAnimation to sample (default: first)
stateMachineNo
individualFramesNoAlso return each sampled frame as a separate full-size image (default false)
Behavior4/5

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

With no annotations supplied, the description carries the full burden. It thoroughly discloses what the tool returns (including the nature of the images, that motion vectors are 'computed from the file data', and the fixed 7-axis checklist). It does not mention failure modes or explicit read-only status, but its output-focused transparency is strong. No contradiction with annotations.

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?

The description is single-paragraph but well-structured with numbered return items (1)-(5) and a clear imperative workflow sentence. Every sentence contributes: purpose, outputs, and usage instructions. No fluff, scannable despite 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?

Given the complexity (7 parameters, no output schema, no annotations), the description is remarkably complete. It explains what the tool produces, how to interpret the visual outputs, what the checklist covers, and how to loop the critique into revision. It even sets an iteration minimum. This is sufficient for an agent to select and execute the tool correctly.

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

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 71%, so the baseline is 3. The description adds meaning to the 'frames' parameter by linking it to 'N frames left→right across the duration' and implies the token-saving intent of 'width' indirectly via 'keep small', but does not explain 'artboard', 'stateMachine', or 'individualFrames' beyond the schema. Overall, moderate additional value.

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 clearly states a specific verb+resource: 'Critique a .riv' via a 'One-call review bundle'. It enumerates the five distinct return types (filmstrip, onion-skin, motion report, metrics+lint, checklist), distinguishing it from sibling render or inspect tools.

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 places the tool in the 'render→critique→revise loop' and gives actionable workflow instructions: 'LOOK at the images, score each axis 1-5, fix anything below 4 (riv_edit / regenerate), then re-run. Iterate at least twice...' It also names alternatives (riv_edit/regenerate), making usage context and next steps unambiguous.

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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