wolfram-prompt

name

wolfram-prompt

description

Author a Wolfram Prompt Repository resource (a deployable LLM Persona, Function, or Modifier prompt) as a literate-markdown document and convert it to the official definition notebook with MarkdownToNotebook. Use this whenever the user wants to create, write, draft, or publish a Wolfram Prompt Repository resource, an LLMPrompt, an LLM persona / function / modifier - especially when they would rather write markdown than hand-edit notebook cells. Also use it when asked to add chat examples, options, or metadata to such a prompt.

Authoring a Prompt Repository resource in markdown

MarkdownToNotebook fills the official Prompt Repository definition notebook (the one CreateNotebook["PromptResource"] opens, with its docked Deploy/Submit toolbar) from a literate-markdown document. A Prompt resource is one of three types - Persona (a chat character), Function (an LLM-backed callable), or Modifier (a post-processor that reshapes another LLM's output) - and each has the same notebook layout, with type-specific slots becoming optional. The author writes YAML frontmatter and ## section headings; the converter chooses every cell style. Use the Prompt template.

Model new documents on the worked example - https://github.com/WolframInstitute/MarkdownToNotebook/blob/main/examples/AdaLovelace.md (a Persona) - and read https://github.com/WolframInstitute/MarkdownToNotebook/blob/main/docs/resource-notebooks.md (the "Prompt" section) for the slot-by-slot mapping.

Read first - the canonical guidelines:

• Prompt Repository submission guidelines: https://resources.wolframcloud.com/PromptRepository/guidelines
• Prompt Repository style guidelines (the rules a submission is reviewed against): https://resources.wolframcloud.com/PromptRepository/style-guidelines
• Wolfram Language code style: https://github.com/WolframInstitute/MarkdownToNotebook/blob/main/GUIDE.md

Frontmatter

Fence a key: value YAML header with --- at the very top:

---
Template: Prompt
ResourceType: Prompt
PromptType: Persona            # Persona | Function | Modifier
Name: CamelCaseName            # noun for Persona, verb for Function, past-tense verb for Modifier
Description: One-line summary that starts with a verb and has no trailing punctuation
ContributedBy: Author Name
Keywords: [keyword one, keyword two]
Categories: [Fictional Characters]    # type-specific list, see below
Topics: [History of Computing, Mathematics]
RelatedSymbols: [LLMPrompt, LLMSynthesize]
RelatedResources: [OtherPromptName]
Links: ["[label](https://example.com)"]
---

Name follows strict per-type grammar - the repository review enforces it:

• Persona - CamelCase noun phrase (Yoda, Wolfie, MockInterviewer, AdaLovelace)
• Function - CamelCase verb phrase (Summarize, CodeWriter, TitleSuggest)
• Modifier - CamelCase past-tense verb (HaikuStyled, Translated, ELI5)

Categories is checkbox-style and the allowed values depend on PromptType:

• Persona categories: Advisor Bots, Character Types, Fictional Characters, Purpose-Based, Roles, Writers, Writing Genres
• Function categories: AI Guidance, Chats, Content Derived from Text, Education, Entertainment, For Fun, General Text Manipulation, Linguistics, Prompt Engineering, Special-Purpose Text Manipulation, Text Analysis, Text Generation, Wolfram Language
• Modifier categories: Computable Output, For Fun, Output Formatting, Personalization, Text Styling

Sections (each ## Heading fills a slot)

Required:

• ## Prompt - the actual prompt body, plain prose. For Function prompts, write named template slots as `{argName}` and they become TemplateSlot placeholders that LLMResourceFunction substitutes at call time. This is the most important part of the resource; the Prompt Repository style guidelines go into detail on writing it well.
• ## Chat Examples - one or more wl cells using the chat-style invocation (ChatEvaluate[..., LLMPrompt["MyPromptName"] ...]) that exercise the persona in a Chat Notebook context. Mark these cells #| eval: false unless a deployed prompt + LLM connection is available at build time.
• ## Basic Examples (and any of the usual Scope, Applications, Properties and Relations, Possible Issues, Neat Examples subsections) - programmatic examples that show the prompt working through LLMSynthesize / LLMResourceFunction rather than a chat session. Same example-section conventions as a Function Resource; for the per-cell authoring rules (one demonstration per cell, :-terminated caption, --- between siblings) see docs/examples.md.

Optional, Persona-only:

• ## Persona Icon - one wl cell that evaluates to an image; becomes the avatar shown in Chat Notebooks.
• ## Cell Processing Function - one wl cell with a pure function applied to every user input cell before the model sees it.
• ## Cell Post Evaluation Function - one wl cell with a pure function applied to the model's output cell after it lands.

Optional, Function-only:

• ## Output Interpreter - one wl cell with the function applied to the model's textual reply to coerce it into a computable result (e.g. ToExpression, an Interpreter).

Optional, any type:

• ## Usage - usage statements, one paragraph per signature (see the Function Resource skill for the `signature` + prose convention).
• ## Details & Options - bulleted notes on how the prompt is configured.
• ## LLM Tools - one wl cell whose value is a list of LLMTool instances the prompt should have access to.
• ## LLM Configuration - one wl cell whose value is the extra LLMConfiguration options (model, temperature, ...).

Code-cell options

A fenced wl cell carries #| option lines at the top (the Quarto cell-option convention), one key: value per line: eval: false (show code without running), file: path (replace the body with a local file or URL), screenshot: true (rasterize a produced Notebook), tear: h (torn-paper screenshot capped to h points), flag: future|excised|.... Record an example's expected result in an <!-- => ... --> comment after the cell. Inline math is $...$. To link a documented symbol inline, wrap an inferred ref in <code>: <code>[Range]()</code> - the empty parens make markdown viewers render it as a clickable link, and the <code> wrapper applies code styling. The converter routes the empty-URL link through linkInferred to a paclet: ref; the -out.md twin further rewrites it to the public web URL.

Examples that load the deployed resource (LLMPrompt["MyPromptName"]) cannot evaluate before the resource exists, and LLMSynthesize / ChatEvaluate need an active LLM connection at evaluation time. Mark these cells #| eval: false so the build does not error; once the prompt is published and the LLM is configured, the cells run as written. (Do not use the LLMPrompt[ResourceObject[EvaluationNotebook[]]] form - EvaluationNotebook[] is the user's notebook at call time, not the deployed resource, so the lookup fails both headlessly and at runtime in a chat session.)

Build & deploy

wolframscript -f build.wls               # converts the .md to .nb

The notebook the converter writes carries the same docked Deploy/Submit toolbar a hand-authored Prompt notebook has; click Submit to the Prompt Repository in the toolbar, or ResourceSubmit[NotebookOpen[\"MyPrompt.nb\"]] from a session, to publish. For a private cloud copy use DeployResource[..., "CloudPublic"].

Check

Before submission, run the docked Check button (top of every resource definition notebook) - it lints the document against the submission guidelines and reports hints by level. Headless, the same lint runs through DefinitionNotebookClientCheckDefinitionNotebook[nbo]` after stamping CellIDs and saving (the headless build does not assign CellIDs, and the scraper needs them to locate cells):

Needs["DefinitionNotebookClient`"]
UsingFrontEnd @ Block[{nbo = NotebookOpen[File["MyResource.nb"]]},
    CurrentValue[nbo, CreateCellID] = True;
    SelectionMove[nbo, All, Notebook];
    FrontEndTokenExecute[nbo, "Save"];
    Normal @ DefinitionNotebookClient`CheckDefinitionNotebook[nbo]
]

Each row is <|"Level" -> ..., "Tag" -> ..., "Parameters" -> ...|> with Level one of Suggestion / Warning / Error. Common tags to address before submission: DescriptionTooLong (shorten to under 128 chars), ExampleTextLastCharacter (end an example caption with :), FoundUnformattedCode (wrap a stray WL symbol in `backticks` or in an inferred link with empty parens like [Range]() (substitute the actual symbol name for Range), ThreeDotEllipsis (use … not ...), NotASystemSymbol (link foreign function-repo names instead of formatting them as system symbols), LargeCellBounds/CellHeight (rasterized output too big - crop it with #| tear: h or shrink the source). The repo's check.wls runs the same lint on every built .nb and prints a per-file summary.