Measure a rendered image or video at a public https URL (max 32 MB / 60 s / 1080p): blur, exposure, black and
frozen frames, flicker, cuts, impacts and colour/lighting drift against reference_image_url. Uses 1 check.
Returns a JSON report plus review frames to check for anatomy/identity defects before calling stg_qa_gate.
| Name | Required | Description | Default |
|---|---|---|---|
| media_url | Yes | ||
| sensitivity | No | ||
| review_frames | No | ||
| reference_image_url | No |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the disclosure burden and does so well: it reveals the 32 MB / 60 s / 1080p input ceilings, the cost model ('Uses 1 check'), and the return shape (JSON report plus review frames). It does not mention authentication or rate-limit behavior, which keeps it short of a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with the core action and constraints, and every clause carries information (defect list, limits, cost, return, workflow). The mid-sentence defect enumeration is dense but not wasteful; the whole thing is one efficient paragraph.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema or annotations exist, so the description correctly fills the void with limits, cost, return content, and workflow ordering relative to stg_qa_gate. The remaining gap is parameter-level meaning for sensitivity/review_frames/media_url, which leaves it slightly short of complete for a 4-param tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 for all four parameters. It gives context for reference_image_url (drift comparison target) and implies review_frames (frames are returned), but media_url is only implicit and 'sensitivity' is never explained, leaving half the parameters semantically ungrounded.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a precise verb (measure/inspect) and resource (rendered image or video at a public https URL) and enumerates the exact defects detected: blur, exposure, black/frozen frames, flicker, cuts, impacts, and colour/lighting drift. It also positions itself relative to the sibling stg_qa_gate, so an agent can distinguish it without opening a schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description establishes the workflow slot clearly: run this 'before calling stg_qa_gate' and use the returned frames to check anatomy/identity defects. It gives input constraints (max 32 MB / 60 s / 1080p) but stops short of explicit when-not-to-use guidance or naming an alternative for oversized/long media.
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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