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nwjnjjj
by nwjnjjj

stg_inspect_render

Analyze rendered images or videos for blur, flicker, black frames, and lighting drift. Returns JSON report and review frames for quality assessment.

Instructions

Measure a rendered image or video (local path, max 32 MB / 60 s / 1080p): blur, exposure, black and frozen frames, flicker, hard cuts, impacts and flashes, and colour/lighting drift against reference_image. Uses 1 check. Returns a JSON report plus review frames — look at them for anatomy/identity defects, then call stg_qa_gate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
sensitivityNo
ignore_issuesNo
review_framesNo
reference_imageNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and discloses important constraints: local path, max 32 MB / 60 s / 1080p, 'Uses 1 check', and that it returns a JSON report plus review frames. It does not discuss permissions, side effects, or rate limits, but the key operational traits are present.

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 purpose, constraints, and measured metrics, then closes with return behavior and next step. It is dense but each clause earns its place, though the metric list is long.

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

Completeness4/5

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

Given no output schema, the description explains the return type and how to use the returned frames. For a five-parameter tool with no annotations, it covers workflow and limits well, but it should do more to explain the optional parameters.

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

Parameters2/5

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

Schema description coverage is 0% across five parameters. The description adds meaning for the required 'path' (local file limits) and for 'reference_image' (colour/lighting drift comparison), but it leaves 'sensitivity', 'ignore_issues', and 'review_frames' unexplained beyond their bare titles.

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 uses a specific verb ('Measure') and resource ('rendered image or video'), then enumerates the exact quality dimensions it checks. It also names the follow-up tool stg_qa_gate, making the tool's role unmistakable.

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

Usage Guidelines4/5

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

It gives clear workflow context: inspect the returned review frames for anatomy/identity defects, then call stg_qa_gate. It does not state when not to use the tool or name alternatives such as stg_detect_events, but the intended usage is well implied.

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