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Hire an AI document layout engine designer

Plan how YAML or JSON data becomes a paged PDF. Get a layout for each section, page-break rules and checks that no field is dropped or split.

What you give

  • The data file, or a sample of it, in YAML, JSON or Markdown front matter
  • The page size, such as A4 or US Letter
  • The kind of document, such as a resume, invoice, spec or proposal

What you get

  • A layout choice for each section of your data, with the reason
  • A plan that keeps every field, including ones no template knew about
  • Page-break rules, so headings and cards stay whole
  • A small layout settings file kept apart from your data

An example

You build a resume, invoice or report maker and users add fields your template does not know.

You ask: “Plan how YAML or JSON data becomes a paged PDF. Use the material I attach and ask for anything essential that is missing.”

You get back:

  • Document type and page. The kind of document and the page size the plan is built for.
  • Field map. Each section of your data, the layout chosen, the reason and how sure the AI is.
  • Unknown or extra fields. Fields no template covers, with the layout picked so none are dropped.

An example, not your task.

Hire this specialist

It is free and needs no account. Download the pack, give it to your AI and tell it the job. Your AI asks for anything it is missing, then does the work and checks it.

Download the specialist

Related specialists

Skills and workflows for this job: Make documents, sheets and slides

Details

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

  • A layout choice for each section of your data, with the reason
  • A plan that keeps every field, including ones no template knew about
  • Page-break rules, so headings and cards stay whole
  • A small layout settings file kept apart from your data
  • Checks to run, and the questions still open

How it does the job well

  • Keep sample code and numbers labelled as examples. Never present untested code as working.
  • Do not claim a layout is the "right" one for a legal, medical or financial document. Say it needs a qualified person to sign off.
  • Prepare plans and code. The user decides what goes into live systems.
  • Say plainly when you do not know. Do not invent library options.
  • Read the existing code, its conventions and its tests before changing anything. Match the project's patterns.
  • Make the smallest change that fully solves the request. Keep unrelated refactors out.
  • Reproduce a bug before fixing it, and add a test that fails without the fix.

Mistakes it avoids

  • Claiming code works without running it or its tests.
  • Inventing APIs, package versions or settings instead of checking the installed ones.
  • Changing behaviour outside the request, such as reformatting whole files or renaming public interfaces.

What a good result looks like

An example, not your task: You build a resume, invoice or report maker and users add fields your template does not know.

  • Document type and page. The kind of document and the page size the plan is built for.
  • Field map. Each section of your data, the layout chosen, the reason and how sure the AI is.
  • Unknown or extra fields. Fields no template covers, with the layout picked so none are dropped.
  • Layout settings file. Sizes, colours and overrides kept apart from your data, matched by section name.
  • Page-break rules. Rules that keep headings with their text and stop cards splitting.
  • Checks. Tests for missing fields and bad page ends, each marked NOT RUN until you run it.

How the work is checked

  • The changed files build, and the relevant tests and linters pass. The commands and results are shown.
  • Each change is explained in one line with its reason, and risky areas are named.
  • Any check that could not run is reported as NOT_RUN with what it needs.
  • States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

Capabilities

  • Read your data. It lists every key and value in your file, with comments and order kept in mind.
  • Measure each section. It checks how alike the records are, how long the text is and whether dates or numbers appear.
  • Choose a layout. It picks cards, timeline, badge row, table or prose for each section, and flags any it is unsure about.
  • Keep layout apart from data. It puts sizes, colours and overrides in a separate settings file, matched to each section by a stable name.
  • Plan the pages. It sets break rules for headings and cards and a split plan if a section is longer than one page.
  • Check the result. It lists tests that no field is missing and no page ends in a stray heading, marked NOT RUN until you run them.

How the role works

  1. Checks your task, context and available tools.
  2. Picks the methods needed and prepares a work plan.
  3. Carries out supported tasks, with each method's limits and review gates.
  4. Checks the real deliverables and corrects supported faults.
  5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id engineering-universal-document-compiler only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/engineering-universal-document-compiler/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

  • The data file, or a sample of it, in YAML, JSON or Markdown front matter
  • The page size, such as A4 or US Letter
  • The kind of document, such as a resume, invoice, spec or proposal
  • The tools you build with, such as React or Node (optional)
  • Fields you must always show, and any layout you already like (optional)

Helpful context (optional)

  • A sample with the oddest fields you have, not the tidiest.
  • A PDF you already like, so it can match the look.

Tools and access

  • Claude Code or another agent with access to your code: It can read your real data files and parser and name the exact place a field gets dropped.
  • Claude, ChatGPT or Gemini in a chat: Good for the layout plan. You paste your sample in and copy changes out yourself.

Functions and deliverables

  • Document layout engine designer: Plan how YAML or JSON data becomes a paged PDF. Get a layout for each section, page-break rules and checks that no field is dropped or split.
    • A layout choice for each section of your data, with the reason
    • A plan that keeps every field, including ones no template knew about
    • Page-break rules, so headings and cards stay whole
    • A small layout settings file kept apart from your data
    • Checks to run, and the questions still open
    Source: Michael Sitarzewski and Agency Agents contributors.
  • JSON document file generator: Build a new PowerPoint, Word, Excel or PDF file from a JSON layout. Get the generated file and basic file checks.
    • A new file in the format you chose
    • The JSON spec behind it
    • Install commands for the package
    • A file you can open and share
    Source: Composio community.
  • Article layout and typo editor: Share rough text or notes. Get a title, summary, headings and lists while body wording stays intact apart from clear typos.
    • A title that says what the reader gets
    • A two-sentence summary taken only from your text
    • The body with headings where the topic changes, and lists where items run in a row
    • A list of what it changed
    • Notes on any unclear lines for you to decide
  • Scanned PDF text reader: Give it PDFs, Office files, or scans. Get page-positioned text and OCR using local tools, with optional OCR services.
    • Text from every page you chose
    • The box position of each piece of text, in JSON
    • OCR text for scanned pages
    • Page images for charts or handwriting (optional)
    • A list of any pages that failed
    Source: K-Dense.
  • AI project context organiser: Share your project and next task. Get a short rules file, a focused file list and a clear handoff for later sessions.
    • A ready rules file for your project
    • A list of which files to load for each task
    • Rules for when to reset or trim the session
    • A checklist for spotting drifting answers
    Source: Addy Osmani.

Tasks you can use it for

  • You build a resume, invoice or report maker and users add fields your template does not know.
  • You have one YAML or JSON file and want it to become a clean, paged document.
  • Your editor and your preview must stay in step, and edits keep wiping comments or the cursor.
  • Long sections split across pages and you want rules to stop it.

Limits to check before starting

  • You want one PDF from text or a sheet with no code. Use the PDF maker and reader or the JSON document file generator.
  • Your problem is blank pages or blurry text in a web-page PDF. Use the PDF layout designer.
  • You need a Word, slide or Excel file. Use the Document generation planner.
  • You need a final contract, medical or financial report. Have a qualified person sign it off, even if this agent plans the layout.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

  • Download the pack from this page and add it to your AI as a skill. If you cannot, paste SKILL.md into a new chat, then paste references/source-agent.md after it.
  • Paste a sample of your data. Say the page size and the kind of document.
  • Type "Plan the layout for each section of this data" or "Find fields this template would drop".
  • Read the layout table first. Fix any section where the AI chose a layout that does not suit it.
  • Run the checks on a real PDF from your own code. The AI cannot render one for you. Ask a developer to review any code before use.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/engineering-universal-document-compiler for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.