pdf

A toolkit for creating and processing PDF files. It covers reports, papers, tables, charts, formulas, code listings, text extraction, form filling, and page operations.

In plain words
What is it for?
Use it to create reports with ReportLab, extract text or tables, fill forms, merge or split pages, rotate or crop documents, and convert eligible Markdown reports into PDFs.
Why use it?
It provides a defined route for both making new PDFs and working with existing ones. It also handles Markdown-to-PDF conversion when the required assembled files and citations are present.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/xyruscode/ai-sync/pdf
Any agent
npx skills add XyrusCode/ai-sync --skill pdf
Clone the repo
git clone --depth 1 https://github.com/XyrusCode/ai-sync

Made for: Claude Code, Codex.

Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,339 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00070 $0.01339
Opus 5 $0.00035 $0.00669
Sonnet 5 $0.00014 $0.00268
Haiku 4.5 $0.00007 $0.00134

Measured yesterday against content hash b5850d326b6f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pdf scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

The scan reads SKILL.md. This mod also ships 8 executable files (scripts/cmd_extract.py, scripts/cmd_form.py, scripts/cmd_inspect.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/pdf/SKILL.md · 133 lines

How it starts

The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Route Selection

Route Trigger Route File
ReportLab (default) All PDF creation requests routes/reportlab.md
md2pdf Convert swarm-assembled Markdown to PDF (gated, see below) routes/md2pdf.md
Process Work with existing PDFs (extract, merge, fill forms, etc.) routes/process.md

Output path: write to the path the user requested. If its directory is not writable (e.g. a container path like /mnt/... that does not exist here), fall back to ./outputs/ under the current working directory, create it, and report the final path. Never fail just because a hardcoded absolute directory is missing.

When to use md2pdf (gate): only for a multi-section Markdown report assembled by a swarm writing skill — i.e. there is a *.agent.final.md or several *_sec{NN}.md files produced by sub-agents, with standard Markdown footnotes ([^id] + [^id]: Title. Date. URL) for citations. For a one-off PDF the user asks you to write, author it natively via the ReportLab route; hand-authored layout is cleaner than converted Markdown.

MANDATORY: Read Route File Before Implementation

Before implementation, you MUST:

  1. Determine the route (ReportLab / md2pdf / Process)
  2. Read the route file (routes/reportlab.md, routes/md2pdf.md, or routes/process.md)
  3. Only then proceed with implementation

This file (SKILL.md) contains constraints and principles. Route files contain how-to details.

When route files use {skill_path}, resolve it in Kimi CLI as:

PDF_SKILL_DIR="${KIMI_PDF_SKILL_DIR:-$(pwd)/.agents/skills/pdf}"

Then replace {skill_path} with "$PDF_SKILL_DIR" in commands.

Decision Rules

User Says Route
"Create a PDF", "Make a report", "Write a paper" ReportLab
"Extract text from PDF", "Merge these PDFs", "Fill this form" Process

Dependencies

Route Libraries
ReportLab pip install reportlab matplotlib
md2pdf pip install markdown2 xhtml2pdf (pure Python, reuses ReportLab)
Process pip install pikepdf pdfplumber
Visual QA Managed pypdfium2 + Pillow

Read the full file on GitHub · 133 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 133 lines · 70 tokens per session scan A b5850d326b6f

Subscribe to this mod's changes

pdf is a skill published in the GitHub repository XyrusCode/ai-sync (2 stars, last pushed 2d ago), licensed MIT. It adds 70 tokens to every session and 1,339 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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