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Fast Video Cataloger

Official

Search videos

search_videos
Read-only

Search your local video catalog by text, keywords, actors, or rating to find videos and clips. Returns entries with id, title, path, and length.

Instructions

Search the user's Fast Video Cataloger catalog - their local library of video files, not cloud storage or the file system. Use this for any question about their videos, footage or clips. Use 'query' for a free text search over titles, descriptions and keywords, or 'keywords' for a comma-separated keyword match. Returns catalog entries including each video's id, title, path and length.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results. Defaults to 25.
queryNoFree text to search for. Leave empty to browse with the other filters.
actorsNoComma-separated actor ids, to find the videos a person appears in. Get ids from search_actors. This is the reverse of get_video_actors.
offsetNoSkip this many results, for paging through a large set.
keywordsNoComma-separated keywords, e.g. 'launch,apollo'. By default a video matches if it carries ANY of them; set matchAllKeywords to require every one.
minRatingNoOnly videos rated at least this (1-5).
matchAllKeywordsNoRequire EVERY keyword rather than any one of them. Use this to narrow a search, e.g. keywords 'beach,sunset' with matchAllKeywords true finds only videos that are both. A keyword that does not exist in the catalog is ignored rather than making the result empty, so check list_keywords if a narrowed search looks too broad.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv10.4.1

TDQS

A4.5/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=true, so the safety profile is covered but little else. The description adds real behavioral content the annotations lack: it enumerates the returned fields (id, title, path, length), which matters because there is no output schema. It does not discuss paging behavior beyond what the schema states.

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?

Three sentences, each carrying distinct load: scope, routing, then return shape. The domain constraint is front-loaded and nothing is repeated from the schema or annotations.

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?

For a read-only, fully schema-documented search tool with no output schema, the description covers scope, usage, mode selection and return fields. An agent has everything needed to call it correctly without further exploration.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3, but the description adds field-level meaning for 'query' (free text over titles, descriptions and keywords) that the schema's generic 'Free text to search for' does not convey, plus a plain-language gloss of the query-vs-keywords choice. The remaining five parameters get no added meaning from the description.

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?

Names a specific verb and resource ('search the user's Fast Video Cataloger catalog') and immediately bounds the domain: local video library, not cloud storage or the file system. That scoping also distinguishes it from siblings like search_transcripts, search_scenes and search_actors without the agent opening any schema.

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

Usage Guidelines4/5

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

Gives explicit context ('use this for any question about their videos, footage or clips') and routes between the two main search modes: 'query' for free text, 'keywords' for keyword matching. It does not name sibling tools or say when a different search tool is the better choice, so it stops short of full when/when-not guidance.

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