菜单
Create, fill, and extract PDFs. Pick the right tool by task — reportlab for data-driven documents, WeasyPrint for HTML/CSS templates, pandoc+Typst for Markdown, and pypdf/pdfplumber for merging, splitting, form-filling, and extraction. Use when the user wants to generate a PDF report, invoice, certificate, or convert content to PDF.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Create professional architecture, workflow, sequence, data-flow, and lifecycle/state diagrams as standalone HTML files with SVG graphics, a built-in dark/light theme toggle, and one-click export to PNG / JPEG / WebP / SVG. Accepts plain-language descriptions or pasted Mermaid code (flowchart, sequenceDiagram, stateDiagram) and lays the diagram out from scratch in archify style. Use when the user asks for system architecture diagrams, infrastructure diagrams, cloud architecture visualizations, security diagrams, network topology, technical workflows, approval flows, runbooks, CI/CD flows, process diagrams, API call sequences, request lifecycles, data pipelines, ETL/ELT maps, PII boundaries, data lineage, state machines, lifecycle diagrams, status transitions, or asks to convert/beautify a Mermaid diagram.
Data analysis methodology — how to frame a question, pick the right technique, avoid statistical traps, and connect results to decisions. NOT a tool tutorial (pandas/polars/duckdb live in python-data-analysis) — this is the judgment layer: problem framing, analysis-type decision tree, experiment/causal design, and domain playbooks (churn, cohort, funnel, anomaly). Trigger: "왜 늘었/줄었지", 이탈 분석, 코호트, 퍼널, A/B 테스트, 인과추론, 상관 vs 인과, 유의성, 세그먼트, 이상 탐지, "이 데이터로 뭘 봐야", 지표 설계, exploratory analysis.
AWS cost management and FinOps practice — Cost Explorer, Budgets, Cost Anomaly Detection, CUR/data exports, cost allocation tags, Cost Categories, Savings Plans vs Reserved Instances, Compute Optimizer / Cost Optimization Hub, rightsizing, unit economics, showback/chargeback. Grounded in the FinOps Foundation Framework (Inform / Optimize / Operate). Trigger: cost anomaly, Savings Plan, Reserved Instance, rightsizing, cost allocation tag, chargeback, showback, unit cost, budget alert, CUR, Cost Explorer, unblended/amortized cost, RI coverage, commitment, "왜 청구서가 늘었지".
Track and report AI model token usage, spending, and budgets from a local cost-tracking database.
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.
| name | pdf-generation |
| description | Create, fill, and extract PDFs. Pick the right tool by task — reportlab for data-driven documents, WeasyPrint for HTML/CSS templates, pandoc+Typst for Markdown, and pypdf/pdfplumber for merging, splitting, form-filling, and extraction. Use when the user wants to generate a PDF report, invoice, certificate, or convert content to PDF. |
| origin | harness |
| workloads | ["writing"] |
Producing a correct PDF starts with choosing the tool that matches the source and the goal. Do not force everything through one library.
| Source / goal | Use | Why |
|---|---|---|
| Data → PDF (invoices, reports, tables, charts) | reportlab | Programmatic, pixel-precise; SimpleDocTemplate/Platypus for flowing docs, Canvas for low-level. |
| HTML/CSS template → PDF | WeasyPrint | Print-CSS fidelity (flexbox, grid, paged media); pair with Jinja2. Needs Python 3.10+. |
| Markdown → PDF (CI, citations) | pandoc + Typst | Typst compiles in milliseconds, no LaTeX package hell; use LaTeX/tectonic only for heavy math. |
| Read / merge / split / forms / extract | pypdf + pdfplumber | pypdf = manipulate/encrypt/watermark; pdfplumber = text + tables with layout. OCR scanned PDFs with pytesseract + pdf2image. |
Rule of thumb: data → reportlab, HTML → WeasyPrint, Markdown → pandoc+Typst, existing PDF → pypdf/pdfplumber.
from reportlab.lib.pagesizes import letter
from reportlab.lib import colors
from reportlab.lib.styles import getSampleStyleSheet
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle
styles = getSampleStyleSheet()
data = [["Name", "Score"], ["Alice", "90"], ["Bob", "85"]]
table = Table(data, hAlign="LEFT")
table.setStyle(TableStyle([
("BACKGROUND", (0, 0), (-1, 0), colors.HexColor("#1E2761")),
("TEXTCOLOR", (0, 0), (-1, 0), colors.white),
("GRID", (0, 0), (-1, -1), 0.5, colors.grey),
]))
SimpleDocTemplate("report.pdf", pagesize=letter).build(
[Paragraph("Report", styles["Title"]), Spacer(1, 12), table]
)
HTML route: weasyprint.HTML(string=rendered_html).write_pdf("out.pdf").
Markdown route: pandoc report.md -o report.pdf --pdf-engine=typst.
₀¹²; they render as solid black rectangles. Use <sub>…</sub> / <super>…</super> XML tags inside a Paragraph, or embed a font that has the glyphs.pdfmetrics.registerFont), or characters silently drop.pdfplumber.open(path).pages[i].extract_table().pypdf.PdfWriter() + append() / page ranges.update_page_form_field_values, or pdf-lib (JS) for complex forms.