pdf-checklist-generator

pdf-checklist-generator is a skill for Claude Code, Codex from HKUDS/OpenSpace. It costs 23 tokens per session (2,121 once invoked), scanned A, original, MIT.

A Python-based workflow for generating structured PDF checklists and reports with sections, tables, and scoring criteria.

In plain words
What is it for?
Use it to create checklists, scorecards, and reports with reportlab, fpdf2, or chart libraries.
Why use it?
It removes the need to lay out these documents manually and provides options for different PDF layouts.

Skill for Claude CodeCodex

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

Good fit Use it to create checklists, scorecards, and reports with reportlab, fpdf2, or chart libraries.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hkuds/openspace/pdf-checklist-generator
About the project

OpenSpace is a skill-management layer for AI agents that stores, retrieves, evaluates, shares, and improves reusable workflows. It is intended for people using multiple coding agents who want skills to be reused and refined based on task outcomes. The catalogue provides 200 skills for use with OpenSpace and the agents it supports.

HKUDS/OpenSpace · 7,534 stars · on GitHub

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 HKUDS/OpenSpace --skill pdf-checklist-generator
Clone the repo
git clone --depth 1 https://github.com/HKUDS/OpenSpace

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-checklist-generator

README.md
[![agentmods](https://agentmods.dev/badge/skills/hkuds/openspace/pdf-checklist-generator.svg)](https://agentmods.dev/skills/hkuds/openspace/pdf-checklist-generator)
Your own site
<a href="https://agentmods.dev/skills/hkuds/openspace/pdf-checklist-generator"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/pdf-checklist-generator.svg" alt="Measured on agentmods" height="20"></a>
Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,121 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00023 $0.02121
Opus 5 $0.00012 $0.01060
Sonnet 5 $0.00005 $0.00424
Haiku 4.5 $0.00002 $0.00212

Measured 4d ago against content hash eea516c48647, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

pdf-checklist-generator 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 4d 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.

benchmarks/gdpval/skills/pdf-checklist-generator/SKILL.md · 274 lines

How it starts

The opening of the file, as written. The whole thing — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PDF Checklist/Report Generator

This skill provides a reusable pattern for creating professional PDF documents (checklists, reports, scorecards) using Python libraries within execute_code_sandbox.

When to Use This Skill

  • Need to generate structured PDF documents programmatically
  • Creating checklists with scoring criteria
  • Building reports with tables, sections, and formatted content
  • Producing downloadable artifacts for workflow tasks

Library Selection

Choose the appropriate library based on your needs:

Library Best For Installation
reportlab Complex layouts, tables, precise control pip install reportlab
fpdf2 Simple documents, easy API pip install fpdf2
matplotlib Charts/graphs in PDFs pip install matplotlib

Step-by-Step Procedure

Step 1: Plan Document Structure

Define the sections, tables, and scoring criteria before coding:

  • Document title and metadata
  • Section headers
  • Table columns and rows
  • Scoring rubric (if applicable)

Step 2: Write Python Code in execute_code_sandbox

Use execute_code_sandbox with the appropriate library. Here are templates:

Template A: Using reportlab (recommended for tables)
from reportlab.lib import colors
from reportlab.lib.pagesizes import letter
from reportlab.platypus import SimpleDocTemplate, Table, TableStyle, Paragraph, Spacer
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import inch

# Create PDF
doc = SimpleDocTemplate("checklist.pdf", pagesize=letter)
elements = []
styles = getSampleStyleSheet()

# Title
title_style = ParagraphStyle('CustomTitle', parent=styles['Heading1'], alignment=1)
elements.append(Paragraph("Compliance Checklist", title_style))
elements.append(Spacer(1, 0.25*inch))

# Create table data
data = [
    ['Criteria', 'Status', 'Score', 'Notes'],
    ['Security Review', 'Pass', '10', 'All checks passed'],
    ['Code Quality', 'Pass', '8', 'Minor improvements'],
    ['Documentation', 'Pending', '5', 'Needs updates'],
]

# Create and style table
table = Table(data, colWidths=[3*inch, 1*inch, 1*inch, 2*inch])
table.setStyle(TableStyle([
    ('BACKGROUND', (0, 0), (-1, 0), colors.grey),
    ('TEXTCOLOR', (0, 0), (-1, 0), colors.whitesmoke),
    ('ALIGN', (0, 0), (-1, -1), 'CENTER'),
    ('GRID', (0, 0), (-1, -1), 1, colors.black),
    ('BACKGROUND', (0, 1), (-1, -1), colors.beige),
]))
elements.append(table)

# Build PDF
doc.build(elements)
print("PDF created: checklist.pdf")
print(f"ARTIFACT_PATH:/workspace/checklist.pdf")

Read the full file on GitHub · 274 lines

Files

What ships with it

1 file 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. 4d ago First seen · 274 lines · 23 tokens per session scan A eea516c48647

Subscribe to this mod's changes

pdf-checklist-generator is a skill published in the GitHub repository HKUDS/OpenSpace (7,534 stars, last pushed 25d ago), licensed MIT. It adds 23 tokens to every session and 2,121 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.

Related

Other skills, from other repositories

pydicom

Use pydicom to read, inspect, write, transform, and safely preflight local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.

K-Dense-AI/scientific-agent-skills · 56 tokens

foundry-hosted-agent-validation

Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.

microsoft/agent-framework · 82 tokens

skill-doc-delivery

Convert markdown to DOCX, PPTX, XLSX, PDF office documents — use when you need exportable deliverables.

nyldn/claude-octopus · 29 tokens

parse-document

Convert a PDF, scan, image of a page, or office file to clean markdown through the connected Superlinked MCP edge, so the source document is not read into model context directly. Use when the user asks to read, parse, OCR, extract from, summarize, or answer questions about a document.

superlinked/sie · 64 tokens

meta-web-to-pdf-briefing

Render a topic into a distributable PDF briefing in three steps: web search → bullet summary → styled PDF. Trigger when the user asks for a PDF briefing on a single topic.

opensquilla/opensquilla · 45 tokens

chat-complex-documents

Chat with and search your complex documents — ask questions, extract tables and fields, and get answers grounded in the source. Connects the hosted Unstructured Transform MCP server to parse, structure, and enrich PDFs, Word/Excel/PowerPoint, images, scanned files, emails, and 60+ other formats into clean, AI-ready…

vellum-ai/vellum-assistant · 90 tokens