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Valmera — agentic AI video editor

by io.valmera
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Watch the video itself

watch_video
Read-only

WATCH THE VIDEO YOURSELF — the real file, pixels and audio, not a description of it. Use this instead of look_at whenever your own model can take video input: look_at sends frames to Valmera's vision model and hands you back a PARAGRAPH, while this hands you the footage. kind 'timeline' (default) is the assembled program as the viewer sees it — it renders the current edit first if it has not been rendered; 'source' is the raw uploaded footage; 'asset' is one uploaded clip (pass asset_key). start/end watch a window rather than the whole thing. It comes back as a direct download link — a plain MP4 you fetch and watch. Cheap: normally it hands over a file that already exists, untouched.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoWatch up to this second.
kindNoDefault 'timeline' — the current edit.
startNoWatch from this second. OUTPUT seconds for 'timeline', source seconds otherwise.
framesNoDefault true. False returns only the video file/link and suppresses sampled frame sheets plus their attached audio; use false for clean external ASR retrieval.
max_mbNoShrink to about this many megabytes. Use when your model has a file-size limit.
renderNokind='timeline': false watches the last render that exists instead of rendering the current edit, and says how stale it is. Default true.
deliveryNoA download link either way. Embedding the file in the reply is off on this deployment.
asset_keyNokind='asset' only: the storage_key list_assets prints.
max_heightNoCap the picture height (e.g. 360). Never up-scales.
project_idYesRequired immutable project scope.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A5/5.0
Behavior5/5

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

Goes beyond annotations by disclosing that it may render the current edit if not already rendered, returns a direct download link, suppresses frame sheets when frames=false, and notes that it is cheap because it usually hands over an existing file. No contradiction with readOnlyHint=true.

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 front-loaded with the core purpose and then systematically covers usage, kinds, parameters, and return format. Every sentence adds value; length is justified by the tool's complexity (10 parameters).

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 complex tool with 10 parameters and no output schema, the description covers all parameter behaviors, the return format (download link), and the cost profile. It also addresses edge cases like stale renders and embedding being off.

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

Parameters5/5

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

Despite 100% schema coverage, the description enriches parameter meaning: explains kind options in detail (timeline renders first, source is raw, asset needs asset_key), clarifies start/end as window boundaries, and explains frames, render, and delivery behavior beyond their schema descriptions.

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 tool's purpose: it delivers the actual video file (pixels and audio) as a download link, contrasting with look_at which returns a paragraph description. It names the specific resource (video) and action (watch) and distinguishes from a sibling tool.

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

Usage Guidelines5/5

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

Explicitly instructs when to use this tool: 'Use this instead of look_at whenever your own model can take video input.' It also explains the difference between timeline/source/asset kinds and when to use each, providing clear selection guidance.

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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