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Glama

analyze_video

Turn a short-form video transcript and optional metadata into structured hook, retention, remix, script, content-gap, and creator-pack insights. No API keys or private platform data required.

Instructions

Analyze short-form video content from a supplied transcript and optional metadata. Does not claim to fetch private or unsupported platform data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nicheNo
titleNo
platformNo
sourceUrlNo
transcriptYesTranscript or captions copied from the video.
durationSecondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.2/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral burden. It adds one negative constraint ('Does not claim to fetch private or unsupported platform data'), but does not describe output format, permissions, rate limits, or whether the operation is read-only. This is minimal disclosure for a tool with six parameters and no output schema.

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 two sentences and front-loads the core purpose. The second sentence is a brief caveat that sets expectations, though it could be seen as defensive. Overall it is concise with no wasted words.

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

Completeness1/5

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

With six parameters, no annotations, no output schema, and very low schema description coverage, the description is far too thin. It does not explain what analysis is produced, how optional metadata influences results, or what the caller should expect to receive. This is inadequate for the tool's complexity.

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

Parameters1/5

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

Schema description coverage is only 17% (only the transcript parameter is documented in the schema), so the description should compensate. It mentions 'supplied transcript and optional metadata' but does not explain the roles of niche, title, platform, sourceUrl, or durationSeconds, leaving most parameters semantically undefined.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a verb ('Analyze') and resource ('short-form video content from a supplied transcript and optional metadata'), but the specific type of analysis is left vague. Sibling tools like analyze_hook and analyze_retention offer more precise analyses, and this tool does not clarify what it analyzes or how it differs from them.

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 guidance on when to use this tool versus alternatives such as analyze_hook or analyze_retention. The second sentence is a disclaimer about not fetching private data, not a usage condition or exclusion.

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