pdf-editing

pdf-editing is a skill for Claude Code, Codex from benchflow-ai/skillsbench. It costs 17 tokens per session (2,777 once invoked), scanned A, original, Apache-2.0.

A Python guide for reading and editing PDF documents with PyMuPDF while keeping their text layer usable. It covers replacing text and permanently removing sensitive text.

In plain words
What is it for?
Use it to update PDF fields, replace existing text in place, and redact confidential information from PDF files.
Why use it?
It helps prevent common editing errors such as leaving old text underneath new text or turning searchable PDFs into images.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to update PDF fields, replace existing text in place, and…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/benchflow-ai/skillsbench/pdf-editing
About the project

SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.

benchflow-ai/skillsbench · 1,747 stars · on GitHub · skillsbench.ai

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.

Any agent
npx skills add benchflow-ai/skillsbench --skill pdf-editing
Clone the repo
git clone --depth 1 https://github.com/benchflow-ai/skillsbench

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for pdf-editing

README.md
[![agentmods](https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/pdf-editing.svg)](https://agentmods.dev/skills/benchflow-ai/skillsbench/pdf-editing)
Your own site
<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/pdf-editing"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/pdf-editing.svg" alt="Measured on agentmods" height="20"></a>
Per session 17 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,777 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00017 $0.02777
Opus 5 $0.00009 $0.01388
Sonnet 5 $0.00003 $0.00555
Haiku 4.5 $0.00002 $0.00278

Measured 3d ago against content hash 7e0f4a10b794, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

pdf-editing 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 3d ago.

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

tasks/edit-pdf/environment/skills/pdf-editing/SKILL.md · 330 lines

How it starts

The opening of the file, as written. The whole thing — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PDF Editing Skill

CRITICAL RULES - READ FIRST

NEVER DO THESE:

  • NEVER use strikethrough lines to cross out text
  • NEVER rasterize or flatten the PDF to images
  • NEVER convert PDF pages to PNG/JPG and draw on them
  • NEVER use pdf-to-image-to-pdf workflows
  • NEVER use add_redact_annot() with BLACK fill (use WHITE fill instead)
  • NEVER add text NEXT TO old values - REPLACE them at the SAME position

TWO APPROACHES - CHOOSE THE RIGHT ONE:

  1. For REPLACING text (e.g., updating name, email, DOB):

    • Use draw_rect() with white fill to cover old text
    • Use insert_text() at the SAME position
    • Text layer is preserved
  2. For TRUE REDACTION of sensitive data (e.g., student ID):

    • Use add_redact_annot(rect, fill=(1,1,1)) with WHITE fill
    • Call apply_redactions() to REMOVE text from PDF structure
    • Then insert_text() to add masked value (e.g., "****5678")
    • Original text is completely removed, not just covered

Overview

USE PYTHON WITH PyMuPDF (fitz) - it is pre-installed and produces the best results.

PyMuPDF preserves the text layer properly, making text extractable after editing. JavaScript libraries like pdf-lib may create text that tools like pypdf cannot extract.

# PyMuPDF is already installed - just use it
python3 -c "import fitz; print('PyMuPDF ready')"

Reading PDF Content

import fitz

doc = fitz.open("input.pdf")
page = doc[0]

# Extract all text to understand the document
text = page.get_text()
print(text)

Finding Text Positions

# search_for() returns list of rectangles where text is found
rects = page.search_for("Label Text")
if rects:
    rect = rects[0]
    # rect.x0, rect.y0 = top-left corner
    # rect.x1, rect.y1 = bottom-right corner
    print(f"Found at: ({rect.x0}, {rect.y0}) to ({rect.x1}, {rect.y1})")

Inserting Text

# Insert text at a specific position
page.insert_text(
    (x_position, y_position),  # coordinates
    "text to insert",
    fontsize=11,
    color=(0, 0, 0)  # black
)

doc.save("output.pdf")

Read the full file on GitHub · 330 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. 3d ago First seen · 330 lines · 17 tokens per session scan A 7e0f4a10b794

Subscribe to this mod's changes

pdf-editing is a skill published in the GitHub repository benchflow-ai/skillsbench (1,747 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 17 tokens to every session and 2,777 once invoked, about $0.0001 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 2026-09-03.