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marcius-llmus

multimodal-reader-mcp

read_media

Analyze local media files by specifying a path, returning structured summaries, timelines, transcripts, and observations.

Instructions

Read a local audio or video file and return structured analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionNo
file_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesGemini model used for the analysis.
summaryYesShort summary of the recording.
questionYesOptional user question that guided the analysis.
timelineYesOrdered timeline entries for key moments.
file_nameYesBasename of the analyzed file.
file_pathYesAbsolute path to the analyzed file.
mime_typeYesDetected MIME type for the analyzed file.
confidenceYesConfidence in the analysis based on media quality and clarity.
transcriptYesSpoken or clearly visible text content.
open_questionsYesUncertainties or missing evidence.
relevant_cluesYesDetails most relevant to the user's question or likely follow-up tasks.
notable_signalsYesErrors, transitions, repeated actions, or unusual signals.
key_observationsYesMost important direct observations from the media.
Behavior3/5

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

The description explicitly indicates a read-only operation on local media files, which is a key behavioral trait. However, it does not mention supported formats, error conditions, or potential limitations, and with no annotations provided, the description only partially carries the transparency burden.

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 a single sentence with no unnecessary words. It is concise and front-loads the core action and purpose.

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?

The description covers the main purpose and output type, but it leaves the 'question' parameter unexplained and provides no usage guidance. The presence of an output schema partially compensates for return value details, but overall the context is not fully complete.

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?

The description implicitly refers to the 'file_path' parameter by mentioning 'local audio or video file', but it says nothing about the 'question' parameter, leaving its purpose completely unexplained. With 0% schema description coverage, the description fails to compensate for the undocumented parameters.

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 action (read), the resource (local audio/video file), and the output (structured analysis). It is specific and unambiguous, and with no sibling tools listed, no differentiation is needed.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool, prerequisites, or when not to use it. There are no alternative tools mentioned, so the usage context is implied but not stated.

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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