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Glama

qa

Analyze game, XR, or app recordings for frame pacing hitches, effective FPS, stereo layout, camera-comfort risks, and flash photosensitivity; returns a summary and chart.

Instructions

Capture QA for a game, XR (VR/AR headset) or app recording: frame pacing (hitches = frames the build failed to deliver while the picture moved, with times and ms; effective fps per second), side-by-side / top-bottom stereo detection, comfort (fast camera turns; pass the headset's horizontal fov_deg for deg/s) and flashes above 3 per second (photosensitivity triage). source = file, URL or watch id. Returns a summary plus a chart.

Input Schema

NameRequiredDescriptionDefault
endNo
startNo
sourceYes
fov_degNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden well: it explains what hitches mean, that effective fps is per second, that flashes above 3/sec are flagged for photosensitivity, and that the result is a summary plus chart. It only leaves out side effects such as whether an analysis artifact is persisted or what permissions/limits apply.

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 front-loaded with the purpose and then packs in the relevant measurement details in a single dense paragraph. Every clause relates to capability, parameter usage, or return value, though the density makes it slightly harder to scan than a bulleted structure.

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

Completeness3/5

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

There is no output schema, so the description must explain returns; it does so minimally with 'Returns a summary plus a chart.' For a four-parameter analysis tool with no annotations, the missing definitions for start/end and the sparse return-value detail leave meaningful gaps.

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 description coverage is 0%, so the description must compensate. It adds useful meaning for source (file, URL, or watch id) and fov_deg (horizontal headset field of view for deg/s comfort analysis), but gives no explanation for start or end, leaving half the parameters undocumented.

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

Purpose4/5

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

The description clearly defines a specific analysis resource: QA of game/XR/app recordings across frame pacing, stereo, comfort, and flash/photosensitivity metrics. It is distinguishable from the sibling tools by its diagnostic focus, though it never explicitly contrasts itself with tools like frame or live_watch_for.

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

Usage Guidelines3/5

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

It implies the tool is for analyzing recordings from a file, URL, or watch id, but does not state when to choose this over alternatives such as frame or live_snapshot. Usage is inferable from the metric list but not explicitly routed.

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