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by KyaniteLabs
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Python
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video_compare_quality

Compares original and processed videos by computing quality metrics such as PSNR and SSIM, helping verify edits and detect visual degradation.

Instructions

Compare video quality between original and processed versions.

Args: original_path: Absolute path to the original/reference video. distorted_path: Absolute path to the processed/distorted video. metrics: Metrics to compute (default: ['psnr', 'ssim']).

Input Schema

NameRequiredDescriptionDefault
metricsNo
overwriteNoExplicitly allow replacing existing media. Existing non-media files are protected.
original_pathYes
distorted_pathYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.16.4
    • addedInput schema / properties / overwrite
      Added value: +{
+  "default": false,
+  "description": "Explicitly allow replacing existing media. Existing non-media files are protected.",
+  "title": "Overwrite",
+  "type": "boolean"
+}
  2. Changed1 schema field changedv1.16.0
    • addedInput schema / additionalProperties
      Added value: +false
  3. Addedv1.5.1

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden and largely fails: it does not say whether the tool is read-only or writes an artifact, what permissions/filesystem access it needs, how long it runs, or what happens on failure. The schema exposes an 'overwrite' flag implying writes/overwrites of existing files, yet the description never mentions the parameter or that side effect.

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 purpose sentence is front-loaded and the Args block is terse, so nothing is wasteful. The brevity is appropriate, though the Args block stops short of covering all schema fields, which is an omission rather than a verbosity problem.

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?

An output schema exists, so return values needn't be explained. Still, for a comparison tool with a mutation-adjacent 'overwrite' flag and no annotations, an agent is left guessing about side effects, supported metric set, and how this differs from the many other quality/QC tools in the sibling list.

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?

With only 25% schema description coverage, the description does compensate for three of the four parameters (original_path, distorted_path, metrics), adding meaning such as 'reference' vs 'distorted'. However it entirely omits 'overwrite' (the one schema-documented param with mutation implications) and never enumerates valid metric names beyond the psnr/ssim default, which also conflicts with the schema default of null.

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 states a specific verb and resource: comparing video quality between an original/reference video and a processed/distorted one. It is clearly more precise than generic siblings like video_quality_check or video_metric_qc, but it never names or distinguishes itself from those siblings, so an agent choosing among several quality tools gets no tiebreaker.

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?

Usage is only implied by the argument names (original vs distorted), which suggests the pre/post-processing comparison scenario. There is no explicit statement of when to prefer this over video_quality_check, video_metric_qc, or video_verdict, and no preconditions or exclusions.

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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