Nodaro DocsPrompts and text
Turn a rough idea into a tested prompt, write a scene-by-scene video script, and let an LLM judge pick the best of several results with Nodaro MCP tools.
The prompt and text tools help an assistant write better input for Nodaro's generation tools and choose between results. enhance_prompt, analyze_prompt and generate_prompt turn a rough idea into a prompt written for a specific node, generate_script writes a video script scene by scene, and reduce merges or judges a list of candidates.
How the LLM calls on this page are charged
Every LLM call on this page is charged for the tokens it actually used, at the rate of the model that ran it. Before the call, Nodaro reserves a hold. A balance below the hold is refused with 402. After the call, you are charged what the call used, which is usually less than the hold. Longer prompts and longer answers cost more. A failure the provider billed, such as a refusal or a cut-off answer, is charged for that usage, and the error says how much. A failure the provider did not bill is refunded. The editor's Run button shows ≈N: an estimate of a typical call on that model. To quote a call on one model before it runs, use list_models with priceIds. See How LLM calls are charged.
enhance_prompt
Rewrites a rough idea into one optimized prompt for a target node type, with no questions in between. Use it for a quick improvement.
Permission: workflows:execute. Credits: one LLM run, charged for the tokens it used at the model's rate (how).
| Parameter | Type | Notes |
|---|---|---|
nodeType | string | Required. The node the prompt is for, such as generate-image, image-to-video or generate-music. |
prompt | string | The rough idea, up to 5,000 characters. Leave it out to start from nothing. |
provider, style, aspectRatio, duration | string or number | The planned model and settings, so the prompt fits them. |
llmModel | string | The LLM that writes the prompt, one of the ids the tool lists, such as gemini-3.6-flash or claude-sonnet-4.6. Leave it out for the default, Gemini 3.6 Flash. |
reasoning_effort | string | none, low, medium, high, xhigh or max. A higher effort usually spends more output tokens, so the call costs more. On a Claude model, any effort runs directly on the model maker's service and is charged at that service's rate. |
advanced_mode | boolean | Gemini and Claude models. Runs the request directly on the model maker's service, so temperature and max_tokens apply. The call is charged per token at that service's rate. Another model returns 400 advanced_mode_unsupported. |
temperature, max_tokens | number | Only with advanced_mode. temperature from 0 to 2, max_tokens up to 32,768. |
Returns: jobId, the prompt, and a recommendedModel when the tool has one.
analyze_prompt
Turns a rough idea into questions with options, for a target node type. Use it with generate_prompt when you want to steer the prompt: answer the questions, then build the prompt from the answers.
Permission: workflows:execute. Credits: one LLM run, charged for the tokens it used at the model's rate (how).
| Parameter | Type | Notes |
|---|---|---|
nodeType | string | Required. The node the prompt is for, such as generate-image. |
prompt | string | The rough idea, up to 5,000 characters. Leave it out to start from nothing. |
| Model and settings | provider, style, aspectRatio, duration, llmModel, reasoning_effort, advanced_mode, temperature and max_tokens, as for enhance_prompt. |
Returns: jobId and questions. Each question has a category, a label, options, the selected option, whether a custom answer is allowed (allowCustom), and whether several answers are allowed (multi).
generate_prompt
Builds one optimized prompt from the answers to the questions of analyze_prompt.
Permission: workflows:execute. Credits: one LLM run, charged for the tokens it used at the model's rate (how).
| Parameter | Type | Notes |
|---|---|---|
nodeType | string | Required. The same node type as in analyze_prompt. |
selections | array | Required. One { category, value, isCustom } per answered question. |
originalPrompt | string | The first idea, up to 5,000 characters, to weave into the result. |
| Model and settings | provider, style, aspectRatio, duration, llmModel, reasoning_effort, advanced_mode, temperature and max_tokens, as for enhance_prompt. |
Returns: jobId, the prompt, and a recommendedModel when the tool has one.
The same prompt wizard is available in the editor and through the REST API.
generate_script
Writes a structured video script from a description: scene-by-scene copy that can drive a series of image or video generations. It works like the Generate Script node.
Permission: workflows:execute. Credits: one LLM run, charged for the tokens it used at the model's rate (how). More scenes or a longer target length write more and cost more.
| Parameter | Type | Notes |
|---|---|---|
prompt | string | Required. What the video is about: topic, style, audience. Up to 10,000 characters. |
model | string | gemini (default), claude or gpt. |
scene_count | integer | The number of scenes, from 1 to 20. Default 5. |
target_duration | integer | The length of the video in seconds, from 5 to 600. Default 60. |
tone | string | The tone, such as dramatic or lighthearted, up to 200 characters. |
style_guide | string | The style the script follows: voice, look and pacing. Up to 100,000 characters. |
Returns: a job id. The script is in the job's output. In clients with MCP Apps, the job card shows it with a Copy button.
reduce
Merges a list of candidates into one result, or has an LLM judge pick the best one. It is the engine of the Choose Best node.
Permission: workflows:execute. Credits: free for the logic strategies. With pick-best-llm, the judge's call is charged for the tokens it used, at the rate of the judge model (how). The default judge is Claude Sonnet 5.5.
| Parameter | Type | Notes |
|---|---|---|
strategyId | string | Required. pick-best-llm, concat, first-non-empty, count, vote or merge-json. |
inputs | array | Required. Up to 1,000 strings: text fragments or URLs. |
strategyConfig | object | The settings of the strategy, below. |
| Strategy | What it does | strategyConfig |
|---|---|---|
pick-best-llm | An LLM judge picks the best candidate against your criteria | criteria (text), inputKind (text or image-url), and an optional llmModel for the judge |
concat | Joins every input | separator |
first-non-empty | Returns the first input that is not empty | none |
count | Counts the inputs | none |
vote | Returns the input that appears most often; a tie goes to the first | caseSensitive |
merge-json | Merges JSON objects | strategy: deep or shallow |
Returns: jobId, the output as a string, and meta.summary, which says what happened. pick-best-llm also returns meta.selectedIndex and meta.reasoning, the judge's explanation.
When the candidates are pictures, set inputKind to image-url. With text, the judge compares the links as text, which looks like a real choice but is not one.
Frequently asked questions
What is the difference between enhance_prompt and analyze_prompt?
enhance_prompt rewrites a rough idea into one optimized prompt in a single call. analyze_prompt returns questions with options first, and generate_prompt builds the prompt from your answers, so you can steer the result.
Do the prompt tools cost credits?
Yes. Each call is one LLM run, charged for the tokens it actually used at the rate of the model that ran it. A hold is reserved before the call, and the call is then charged what it used. Longer prompts and longer answers cost more.
How can an assistant choose the best of several images?
Call reduce with the strategy pick-best-llm, the image URLs as inputs, inputKind set to image-url, and your criteria. The judge returns the winner, its index and its reasoning.
Related
MCP tools reference
Generate Script
Choose Best
Prompt Wizard
Last updated on
Pipelines
Start a Story to Video pipeline from a prompt, watch its stages, approve or refine them in chat, and branch a finished pipeline from any stage with MCP tools.
Image
Generate, transform, edit, mask, composite and describe images from an AI assistant with the Nodaro image tools, their parameters, defaults and credits.