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Generate an AI image story video

generate_image_story
Destructive

CREATES an AI image story: a narrated script turned into a sequence of AI-generated images, read aloud with captions over it. Suited to facts, history, horror, storytime and explainers. YOU WRITE THE SCRIPT, AND ONLY THE SCRIPT: the text you send is the narration that is spoken, verbatim, in that order (get_recipe image-story has the writing advice and a worked example). Show it to the user as plain text before spending anything and change it until they like it (iterating is free). Never write the pictures: aicut cuts your script into scenes and writes every image prompt itself. PRICE IS DRIVEN BY THE IMAGE COUNT, not the words: estimate_only: true returns scene_count and voice_provider beside the money, so say the count and the price. The levers: seconds_per_image (3 default; 5 is cheaper, 2 dearer), image_model (zit-realism is the default; gpt-image-2.5 has the highest per-image price, so quote it before using it) and voice_provider (the two voice services are priced differently). Re-quote after changing any of them or adding a style_id (list_image_story_styles: it forces the expensive edit-capable image model). AFTER: this one call makes the finished video (the answer carries scene_count, the price split and renders_automatically: true; no fire or render step). Wait with wait_for_generation; when terminal get_video carries the file url. start_confirmed: false means the job exists but its start was never confirmed: do not create it again, watch it, and tell the user it may need a retry if it has not moved in fifteen minutes. LANGUAGE: a script not in language is TRANSLATED, so a quote is exact only for the script you sent. A script over the language's character limit is refused (aicut will NOT cut it); too many images for one video: use a longer seconds_per_image. SPENDS TOKENS: price with estimate_only: true, ask in the SAME message as the price, and wait for a go that names THIS purchase (SPENDING RULES, this server's instructions). IDEMPOTENCY: a reused idempotency_key REPLAYS the first job whatever the settings: never reuse one for a new generation (this server's instructions).

Input Schema

NameRequiredDescriptionDefault
textYesThe narration script in plain prose: what the voice says, start to finish. No scene markers, image directions or speaker labels; aicut cuts it into scenes and writes every image itself.
voiceNoThe narrator's voice. The voice id, in the provider named by `voice_provider`; omit for that provider's default narrator. openai: alloy, ash, ballad, coral, echo, sage, shimmer, verse (`ash` reads deepest, `shimmer` and `sage` lighter; retired `onyx`, `nova`, `fable` still work, speaking as `ash`, `shimmer`, `alloy`). elevenlabs: an id from `list_voices` with `provider: 'elevenlabs'` (stock, cloned or custom voices; PAGED: pass `limit: 100` and read `has_more` before saying a voice does not exist). Any other id is refused uncharged. Cloned and custom ElevenLabs voices ARE accepted here and on `generate_fake_text_video`; `generate_audio` cannot.
languageNoThe language `text` is written in, by name; default English. Naming another language makes aicut translate the script, which changes its length and the price.
style_idNoAn authored look from `list_image_story_styles`. It forces the expensive edit-capable image model, so re-quote. Omit for aicut's default photorealistic look.
image_modelNoThe look of the images; default `zit-realism` (photoreal, cheapest). `zit-lora-*` and `zit-comic` are illustrated looks at the same price, `flux-klein*` cost more, `gpt-image-2.5` is the priciest: quote it before you pick it.
aspect_ratioNoDefaults to `9:16`, the vertical shape every short-form platform wants.
caption_styleNoHow the burned-in captions look; default `karaoke`; `none` turns them off.
estimate_onlyNoPrice only; creates nothing.
sound_effectsNoAn ambient sound effect per scene. Defaults to false, and it ADDS to the price by the video's length: quote it.
voice_providerNoWhich voice service reads the narration. `openai` (the default) or `elevenlabs`. The two voice services are priced differently, so call `estimate_only` again after changing it.
idempotency_keyNoRetry-safety key (IDEMPOTENCY).
caption_positionNoWhere the captions sit; default `bottom`.
image_resolutionNoDefaults to `standard`. `high` selects the model's high-resolution price row (for some models both rows cost the same).
seconds_per_imageNoHow long each image stays on screen; default 3. THE MAIN PRICE LEVER: 5 buys roughly 40% fewer images than 3 for the same script, 2 buys 50% more.
transition_soundsNoA whoosh between scenes. Defaults to false; free.
transition_effectsNoA visual slide between scenes. Defaults to false; free.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations mark this destructive/idempotent=false, and the description backs that up with concrete spend semantics (price levers, what each lever does to image count), the idempotency replay hazard, translation/character-limit refusal behaviour, and the start_confirmed:false recovery rule. It also discloses that this single call renders the video with no separate fire/render step, which is essential behaviour an agent could not infer.

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?

Front-loaded with purpose and the write-the-script rule, then organised into pricing, post-call, language and idempotency sections. Dense and heavily capitalised for a costly tool, which is defensible, but the wall-of-prose density and shouting reduce scannability slightly.

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 16-parameter, spend-incurring, open-world generator with no output schema, the description covers what is produced, how the result is retrieved (wait_for_generation then get_video), failure states, and refusal conditions. Nothing an agent needs to invoke it safely is missing.

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 adds real decision value by ranking the price levers (seconds_per_image 5 is ~40% cheaper than 3, 2 is ~50% dearer; gpt-image-2.5 is priciest, quote it; style_id forces the expensive model). Some of this restates the schema descriptions, so it is not pure addition, but the trade-off framing exceeds the schema.

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?

Opens with a specific verb and concrete output: a narrated script turned into AI-generated images with captions. Crucially it states the division of labour ('YOU WRITE THE SCRIPT, AND ONLY THE SCRIPT... never write the pictures'), which separates this from script-and-prompt siblings like generate_story_video. An agent can tell what it produces and what its own input responsibility is without opening the schema.

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?

Explicit about the pre-call workflow: show the script to the user as plain text, iterate for free, price with estimate_only, quote the scene count and price, ask for a go naming this purchase. It also routes to get_recipe for writing advice and list_image_story_styles for styles, and names the post-call path (wait_for_generation, then get_video).

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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Directories

Listed in ChatGPT · aicut

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