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by ai.switchapp
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Full Video Analysis

analyze_video_report

Run the FULL Switch Vision analysis on a video, the same premium report the Video Analysis page produces: it watches AND listens in three forensic passes and returns a structured report with every category: overview (scores and takeaways), a second by second timeline, audio, visual craft, story and retention, speech transcript, ready to run recreation prompts, and metadata. Pass video_url (a public https video URL, YouTube included) OR one of your own Switch video ids. For an external file also pass duration_seconds (YouTube and your own videos are measured automatically) because the analysis is billed per second of the file, 3 tokens per second with a 30 second minimum. Re-running the same video and question returns the existing report without charging again. Optional question focuses the analysis. Returns a report_id right away; poll get_vision_report until status is succeeded (a few minutes). If it cannot finish, your tokens are returned automatically. For one quick question about a video use analyze_video instead; this tool is the full paid report.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
forceNoOptional. Re-running the same video and question returns the existing report without charging again; pass true to force a fresh, freshly billed analysis.
questionNoOptional. Something to pay special attention to.
video_urlYesA public https video URL (YouTube ok), OR one of your own Switch video ids.
duration_secondsNoLength in seconds. Required for external files; YouTube and your own Switch videos are measured automatically.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / force
      Added value: +{
+  "description": "Optional. Re-running the same video and question returns the existing report without charging again; pass true to force a fresh, freshly billed analysis.",
+  "type": "boolean"
+}
  2. Added

TDQS

A5/5.0
Behavior5/5

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

Beyond the readOnlyHint=false annotation, the description discloses significant behavioral traits: it bills per second with a 30-second minimum, re-running the same video/question is not charged again (with force to override), it returns a report_id immediately rather than a synchronous result, and tokens are returned automatically if it cannot finish. This is exactly the context an agent needs to manage expectations.

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 dense but every sentence earns its place. It front-loads the core purpose, then logically flows through inputs, billing, re-run behavior, return type, polling, failure handling, and alternatives. No filler words; the length is justified by the tool's complexity.

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 no output schema, the description adequately covers return semantics (report_id + polling via get_vision_report) and lists the report's content categories. It also explains billing constraints, the cached-result behavior, and the distinction from the lighter analyze_video tool. This is a well-rounded description for a complex tool.

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

Parameters5/5

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

Although the schema already documents all four parameters, the description enriches meaning by explaining duration_seconds is required for external files but auto-measured for YouTube/Switch videos, and that the 'force' parameter overrides the default cached-report behavior. This clarifies real-world usage beyond the schema's field-level definitions.

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 the tool runs the full Switch Vision analysis on a video, producing a premium report with specific categories (overview, timeline, audio, visual craft, story/retention, transcript, prompts, metadata). It explicitly contrasts with the sibling analyze_video tool, making its unique purpose unmistakable.

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?

Provides explicit when-to-use guidance: use for full paid report vs. analyze_video for quick questions. Details input options (public URL or Switch video id), duration_seconds requirement for external files, billing rules (3 tokens/sec, 30s minimum), and the polling flow via get_vision_report. This is comprehensive and directly actionable.

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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