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watch

Analyze local videos or platform URLs to return timestamped evidence and an overview index; set start/end to process only a relevant segment of long recordings.

Instructions

Analyse a local video file or URL (YouTube, Vimeo, TikTok, X, Instagram...). mode: auto | film | screen (screen = app/screen recordings). start/end ("12:30", "1:02:00", or seconds) watch only a window, and a URL downloads only that part: use it for long videos when the question is about one stretch. Times stay in full-video time. cookies_from_browser ("chrome", "safari", ...) is for login-gated URLs, only with the user's OK. Returns INDEX.md plus the first overview contact sheet. First run takes ~1-2 s per minute.

Input Schema

NameRequiredDescriptionDefault
endNo
modeNoauto
forceNo
startNo
sourceYes
cookies_from_browserNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

A4/5.0
Behavior4/5

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

With no annotations at all, the description carries the full burden and does well: it discloses the return value (INDEX.md plus first overview contact sheet), performance cost (~1-2 s per minute on first run), and auth behavior for gated URLs. The 'force' behavior and whether results are cached on subsequent runs are left unexplained.

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?

Purpose is front-loaded in the first sentence and the remaining lines each add a distinct fact (mode, windowing, cookies, return value, cost). It is dense but not padded; the middle sentence is a long run-on that slightly hurts scannability.

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

Completeness4/5

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

There is no output schema and no annotations, so the description correctly compensates by naming the returned artifacts and noting the initial processing time. The unexplained 'force' flag is the one remaining gap for an agent deciding how to call it.

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 coverage is 0%, so the description must compensate, and it does for 5 of 6 parameters: mode values (auto | film | screen with screen explained), start/end accepted formats plus the key semantic that 'times stay in full-video time', and cookies_from_browser values/conditions. Only 'force' receives no explanation.

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

Purpose4/5

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

The first sentence gives a specific verb and resource ('Analyse a local video file or URL') and enumerates supported platforms, which makes the opaque name 'watch' unambiguous. It does not explicitly distinguish itself from siblings like frame, look, or live_watch_for, so it stops short of a 5.

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?

Offers concrete when-to-use guidance: start/end windowing is recommended 'for long videos when the question is about one stretch', and cookies_from_browser is restricted to login-gated URLs 'only with the user's OK'. No sibling alternatives are named for choosing between watch and frame/zoom/look, so it is clear context without explicit routing.

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