Agent skill
minimax-pdf
Use this skill when visual quality and design identity matter for a PDF. CREATE (generate from scratch): "make a PDF", "generate a report", "write a proposal", "create a resume", "beautiful PDF", "professional document", "cover page", "polished PDF", "client-ready document". FILL (complete form fields): "fill in the form", "fill out this PDF", "complete the form fields", "write values into PDF", "what fields does this PDF have". REFORMAT (apply design to an existing doc): "reformat this document", "apply our style", "convert this Markdown/text to PDF", "make this doc look good", "re-style this PDF". This skill uses a token-based design system: color, typography, and spacing are derived from the document type and flow through every page. The output is print-ready. Prefer this skill when appearance matters, not just when any PDF output is needed.
Install this agent skill to your Project
npx add-skill https://github.com/mxyhi/ok-skills/tree/main/minimax-pdf
Metadata
Additional technical details for this skill
- version
- 1.0
- category
- document-generation
SKILL.md
minimax-pdf
Three tasks. One skill.
Read design/design.md before any CREATE or REFORMAT work.
Route table
| User intent | Route | Scripts used |
|---|---|---|
| Generate a new PDF from scratch | CREATE | palette.py → cover.py → render_cover.js → render_body.py → merge.py |
| Fill / complete form fields in an existing PDF | FILL | fill_inspect.py → fill_write.py |
| Reformat / re-style an existing document | REFORMAT | reformat_parse.py → then full CREATE pipeline |
Rule: when in doubt between CREATE and REFORMAT, ask whether the user has an existing document to start from. If yes → REFORMAT. If no → CREATE.
Route A: CREATE
Full pipeline — content → design tokens → cover → body → merged PDF.
bash scripts/make.sh run \
--title "Q3 Strategy Review" --type proposal \
--author "Strategy Team" --date "October 2025" \
--accent "#2D5F8A" \
--content content.json --out report.pdf
Doc types: report · proposal · resume · portfolio · academic · general · minimal · stripe · diagonal · frame · editorial · magazine · darkroom · terminal · poster
| Type | Cover pattern | Visual identity |
|---|---|---|
report |
fullbleed |
Dark bg, dot grid, Playfair Display |
proposal |
split |
Left panel + right geometric, Syne |
resume |
typographic |
Oversized first-word, DM Serif Display |
portfolio |
atmospheric |
Near-black, radial glow, Fraunces |
academic |
typographic |
Light bg, classical serif, EB Garamond |
general |
fullbleed |
Dark slate, Outfit |
minimal |
minimal |
White + single 8px accent bar, Cormorant Garamond |
stripe |
stripe |
3 bold horizontal color bands, Barlow Condensed |
diagonal |
diagonal |
SVG angled cut, dark/light halves, Montserrat |
frame |
frame |
Inset border, corner ornaments, Cormorant |
editorial |
editorial |
Ghost letter, all-caps title, Bebas Neue |
magazine |
magazine |
Warm cream bg, centered stack, hero image, Playfair Display |
darkroom |
darkroom |
Navy bg, centered stack, grayscale image, Playfair Display |
terminal |
terminal |
Near-black, grid lines, monospace, neon green |
poster |
poster |
White bg, thick sidebar, oversized title, Barlow Condensed |
Cover extras (inject into tokens via --abstract, --cover-image):
--abstract "text"— abstract text block on the cover (magazine/darkroom)--cover-image "url"— hero image URL/path (magazine, darkroom, poster)
Color overrides — always choose these based on document content:
--accent "#HEX"— override the accent color;accent_ltis auto-derived by lightening toward white--cover-bg "#HEX"— override the cover background color
Accent color selection guidance:
You have creative authority over the accent color. Pick it from the document's semantic context — title, industry, purpose, audience — not from generic "safe" choices. The accent appears on section rules, callout bars, table headers, and the cover: it carries the document's visual identity.
| Context | Suggested accent range |
|---|---|
| Legal / compliance / finance | Deep navy #1C3A5E, charcoal #2E3440, slate #3D4C5E |
| Healthcare / medical | Teal-green #2A6B5A, cool green #3A7D6A |
| Technology / engineering | Steel blue #2D5F8A, indigo #3D4F8A |
| Environmental / sustainability | Forest #2E5E3A, olive #4A5E2A |
| Creative / arts / culture | Burgundy #6B2A35, plum #5A2A6B, terracotta #8A3A2A |
| Academic / research | Deep teal #2A5A6B, library blue #2A4A6B |
| Corporate / neutral | Slate #3D4A5A, graphite #444C56 |
| Luxury / premium | Warm black #1A1208, deep bronze #4A3820 |
Rule: choose a color that a thoughtful designer would select for this specific document — not the type's default. Muted, desaturated tones work best; avoid vivid primaries. When in doubt, go darker and more neutral.
content.json block types:
| Block | Usage | Key fields |
|---|---|---|
h1 |
Section heading + accent rule | text |
h2 |
Subsection heading | text |
h3 |
Sub-subsection (bold) | text |
body |
Justified paragraph; supports <b> <i> markup |
text |
bullet |
Unordered list item (• prefix) | text |
numbered |
Ordered list item — counter auto-resets on non-numbered blocks | text |
callout |
Highlighted insight box with accent left bar | text |
table |
Data table — accent header, alternating row tints | headers, rows, col_widths?, caption? |
image |
Embedded image scaled to column width | path/src, caption? |
figure |
Image with auto-numbered "Figure N:" caption | path/src, caption? |
code |
Monospace code block with accent left border | text, language? |
math |
Display math — LaTeX syntax via matplotlib mathtext | text, label?, caption? |
chart |
Bar / line / pie chart rendered with matplotlib | chart_type, labels, datasets, title?, x_label?, y_label?, caption?, figure? |
flowchart |
Process diagram with nodes + edges via matplotlib | nodes, edges, caption?, figure? |
bibliography |
Numbered reference list with hanging indent | items [{id, text}], title? |
divider |
Accent-colored full-width rule | — |
caption |
Small muted label | text |
pagebreak |
Force a new page | — |
spacer |
Vertical whitespace | pt (default 12) |
chart / flowchart schemas:
{"type":"chart","chart_type":"bar","labels":["Q1","Q2","Q3","Q4"],
"datasets":[{"label":"Revenue","values":[120,145,132,178]}],"caption":"Q results"}
{"type":"flowchart",
"nodes":[{"id":"s","label":"Start","shape":"oval"},
{"id":"p","label":"Process","shape":"rect"},
{"id":"d","label":"Valid?","shape":"diamond"},
{"id":"e","label":"End","shape":"oval"}],
"edges":[{"from":"s","to":"p"},{"from":"p","to":"d"},
{"from":"d","to":"e","label":"Yes"},{"from":"d","to":"p","label":"No"}]}
{"type":"bibliography","items":[
{"id":"1","text":"Author (Year). Title. Publisher."}]}
Route B: FILL
Fill form fields in an existing PDF without altering layout or design.
# Step 1: inspect
python3 scripts/fill_inspect.py --input form.pdf
# Step 2: fill
python3 scripts/fill_write.py --input form.pdf --out filled.pdf \
--values '{"FirstName": "Jane", "Agree": "true", "Country": "US"}'
| Field type | Value format |
|---|---|
text |
Any string |
checkbox |
"true" or "false" |
dropdown |
Must match a choice value from inspect output |
radio |
Must match a radio value (often starts with /) |
Always run fill_inspect.py first to get exact field names.
Route C: REFORMAT
Parse an existing document → content.json → CREATE pipeline.
bash scripts/make.sh reformat \
--input source.md --title "My Report" --type report --out output.pdf
Supported input formats: .md .txt .pdf .json
Environment
bash scripts/make.sh check # verify all deps
bash scripts/make.sh fix # auto-install missing deps
bash scripts/make.sh demo # build a sample PDF
| Tool | Used by | Install |
|---|---|---|
| Python 3.9+ | all .py scripts |
system |
reportlab |
render_body.py |
pip install reportlab |
pypdf |
fill, merge, reformat | pip install pypdf |
| Node.js 18+ | render_cover.js |
system |
playwright + Chromium |
render_cover.js |
npm install -g playwright && npx playwright install chromium |
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
ai-elements
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
opensrc
Fetch dependency source code to give AI agents deeper implementation context. Use when the agent needs to understand how a library works internally, read source code for a package, fetch implementation details for a dependency, or explore how an npm/PyPI/crates.io package is built. Triggers include "fetch source for", "read the source of", "how does X work internally", "get the implementation of", "opensrc path", or any task requiring access to dependency source code beyond types and docs.
test-driven-development
Use when implementing any feature or bugfix, before writing implementation code
dogfood
Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.
get-api-docs
Use this skill when you need documentation for a third-party library, SDK, or API before writing code that uses it — for example, "use the OpenAI API", "call the Stripe API", "use the Anthropic SDK", "query Pinecone", or any time the user asks you to write code against an external service and you need current API reference. Fetch the docs with chub before answering, rather than relying on training knowledge.
prompt-engineering-patterns
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.
Didn't find tool you were looking for?