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Edit a video

edit_video

Change a short video with words: swap the subject, outfit, setting, style or weather while keeping the motion. OAuth uses site credits (from 127 credits per second with the default model). API keys use a separate USD wallet. Omit approval to get a quote, then confirm max_credits for OAuth or currency USD and decimal max_usd for API keys.

Input Schema

NameRequiredDescriptionDefault
modelNoOptional model that can edit videos (list_models with category video shows them). Leave empty for the default, Kling O3.
promptYesWhat to change, in plain words: the subject, outfit, setting, style or weather. What you don't mention stays the same.
max_usdNoAPI key only: maximum approved USD as a decimal string with up to 9 fractional digits. Set currency to USD. Only set after the user confirms the quoted cost_usd. Never convert max_credits.
currencyNoBilling unit: USD for API keys; credits for OAuth (optional for existing OAuth clients).
video_urlYesThe clip to change (3 to 10 seconds works best): a popnow:// link from an earlier result, or a public https link.
max_creditsNoOAuth only: the most site credits the user agreed to spend on this. Only set it after the user confirmed a quoted price.
reference_image_urlsNoOptional reference pictures (https or popnow:// links) for a new character, outfit, object or place.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Beyond the annotations (which only mark it as non-read-only, open-world, non-idempotent, non-destructive), the description discloses pricing (127 credits/second baseline), two separate billing wallets by auth method, and a quote-before-charge confirmation flow — genuinely valuable behavior. The weakness is the phrase 'Omit approval', which does not correspond to any parameter name, leaving the agent to work out that approval means omitting max_credits/max_usd.

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?

Three compact sentences: capability first, billing second, confirmation procedure last — well front-loaded with no filler. The only friction is the undefined term 'approval', which forces a reread against the schema to map onto concrete fields.

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?

For a 7-parameter mutation tool with no output schema, the description covers cost, auth branching, and input clip length well. It never says what a call returns — a job id, a quote object with cost_usd, or a finished asset — even though the quote flow depends on the agent reading cost_usd from that response, which is a meaningful gap for correct multi-step invocation.

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 100%, so the baseline is 3; the description earns slightly more by tying parameters to a workflow (quote first, then confirm max_credits or max_usd) and by supplying the per-second pricing that has no schema equivalent. It does not explain model selection or reference_image_urls beyond what the schema already says, so the added meaning is real but partial.

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 description uses a specific verb and resource ('Change a short video with words') and enumerates the editable dimensions (subject, outfit, setting, style, weather) while constraining behavior ('keeping the motion'). That scope implicitly separates it from siblings like change_camera_angle, copy_motion, and extend_video, but it never names an alternative, so an agent must still infer the boundary itself.

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?

It clearly explains the two-step usage pattern: call without approval to obtain a quote, then re-call with max_credits (OAuth) or currency USD plus max_usd (API keys) to confirm. It also branches guidance by auth type. It stops short of saying when to prefer this tool over edit_image or the other video siblings, so the routing guidance is contextual rather than explicit.

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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