gemini-document-processing

A guide for using Google's Gemini API to process PDF documents with visual understanding. It covers extracting text, images, diagrams, charts, and tables from PDFs and turning them into structured information.

In plain words
What is it for?
Analysing PDFs, extracting their contents, summarising them, answering questions about them, and converting them into structured formats.
Why use it?
It helps an agent handle PDFs whose meaning depends on layout, images, or tables rather than treating them as plain text alone.

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/einverne/dotfiles/gemini-document-processing
Any agent
npx skills add einverne/dotfiles --skill gemini-document-processing
Clone the repo
git clone --depth 1 https://github.com/einverne/dotfiles

Made for: Claude Code, Codex.

Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,544 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00061 $0.01544
Opus 5 $0.00030 $0.00772
Sonnet 5 $0.00012 $0.00309
Haiku 4.5 $0.00006 $0.00154

Measured 2d ago against content hash 5a4cc9adac67, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gemini-document-processing 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 2d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/check-api-key.sh, scripts/process-document.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.

claude/skills/gemini-document-processing/SKILL.md · 230 lines

The source is not reproduced here

Licensed GPL-3.0

The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Files

What ships with it

8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 2d ago First seen · 230 lines · 61 tokens per session scan A 5a4cc9adac67

Subscribe to this mod's changes

gemini-document-processing is a skill published in the GitHub repository einverne/dotfiles (121 stars, last pushed 4d ago), licensed GPL-3.0. It adds 61 tokens to every session and 1,544 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 2026-08-30.

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