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Glama

query

Locate time ranges in indexed videos by matching speech transcripts, visual content, or event patterns like silence, black frames, or loud audio. Returns moments for editing or review.

Instructions

Find time ranges. kind: speech (exact+fuzzy transcript match), visual (CLIP text->shot), event (e.g. "silence>1.5", "black", "loud", "freeze"), any (event syntax, else speech+visual).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoany
textYes
limitNo
video_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose matching behavior ('exact+fuzzy transcript match', 'CLIP text->shot', 'silence>1.5', 'freeze'), which is genuine behavioral context, but it omits that this is a read-only search, how many results come back (limit is never mentioned), and any pagination or ordering behavior.

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?

Dense and front-loaded: the purpose leads, then each kind is defined inline with no filler sentences. It borders on cryptic for the opening clause ('Find time ranges'), which costs a point.

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?

An output schema exists, so return values need no explanation, and the four kinds are well covered. However, limit/pagination behavior is absent, and for a tool whose output feeds siblings like get_segment, the description leaves the agent without enough to call it confidently beyond the default kind='any'.

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

Parameters3/5

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. It does explain the semantically complex parameter (kind) in detail, including accepted values and fallback behavior, plus event syntax examples — but text, video_id and especially limit (default 10, undocumented) receive no explanation, so the compensation is only partial.

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 verb+resource pair ('Find time ranges') is terse and never states that the search operates over the video identified by video_id, though the kind definitions (transcript match, CLIP text->shot) let an agent infer it is a content search. It does not differentiate itself from siblings like get_segment or overview, so the agent must guess where this fits in the workflow.

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

Usage Guidelines3/5

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

Usage is implied through the kind semantics: 'any' falls back to event syntax then speech+visual, and the event examples hint at when event matching applies. There is no explicit when-to-use/when-not guidance and no routing toward siblings such as get_segment for retrieving the actual matched range.

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