pdf-extraction-fallbacks

pdf-extraction-fallbacks is a skill for Claude Code, Codex from HKUDS/OpenSpace. It costs 22 tokens per session (1,953 once invoked), scanned A, original, MIT.

A PDF extraction process that validates downloads, tries several text-extraction tools, and records which method worked.

In plain words
What is it for?
It helps extract text from regulatory documents, handbooks, and other PDFs that require multiple attempts.
Why use it?
Protected, corrupted, or unusually encoded PDFs can make a single approach unreliable. Early checks and documented fallbacks help avoid treating failed extraction as complete.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit It helps extract text from regulatory documents, handbooks, and other PDFs that require multiple attempts.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hkuds/openspace/pdf-extraction-fallbacks
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-extraction-fallbacks
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-extraction-fallbacks

README.md
[![agentmods](https://agentmods.dev/badge/skills/hkuds/openspace/pdf-extraction-fallbacks.svg)](https://agentmods.dev/skills/hkuds/openspace/pdf-extraction-fallbacks)
Your own site
<a href="https://agentmods.dev/skills/hkuds/openspace/pdf-extraction-fallbacks"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/pdf-extraction-fallbacks.svg" alt="Measured on agentmods" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,953 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00022 $0.01953
Opus 5 $0.00011 $0.00977
Sonnet 5 $0.00004 $0.00391
Haiku 4.5 $0.00002 $0.00195

Measured 3d ago against content hash 8fd00e9806da, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

pdf-extraction-fallbacks scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -L -o document.pdf "$URL"
benchmarks/gdpval/skills/pdf-extraction-fallbacks/SKILL.md · 257 lines

How it starts

The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.

PDF Extraction with Multi-Fallback Strategy

Purpose

When extracting text from PDFs (especially regulatory documents, handbooks, or protected content), single-method approaches often fail due to JavaScript protection, CORS restrictions, encoding issues, or corrupted downloads. This skill provides a robust multi-fallback workflow that detects failures early and tries sequential extraction methods.

Core Pattern

  1. Download with validation - Check file size and content sanity immediately
  2. Sequential extraction attempts - Try multiple tools in order of reliability
  3. Early failure detection - Don't proceed with obviously corrupt files
  4. Document fallback path - Log which method succeeded for future reference

Step-by-Step Instructions

Step 1: Download and Validate

Before attempting extraction, validate the downloaded file:

# Download the PDF
curl -L -o document.pdf "$URL"

# Check file size (reject if < 1KB - likely error page)
FILE_SIZE=$(stat -f%z document.pdf 2>/dev/null || stat -c%s document.pdf 2>/dev/null)
if [ "$FILE_SIZE" -lt 1024 ]; then
    echo "ERROR: File too small ($FILE_SIZE bytes) - likely not a valid PDF"
    # Check if it's an HTML error page
    head -c 200 document.pdf | grep -i "<html\|<!doctype\|error\|access denied" && \
        echo "Detected HTML error page instead of PDF"
    exit 1
fi

# Check PDF magic bytes
HEAD_BYTES=$(head -c 4 document.pdf)
if [ "$HEAD_BYTES" != "%PDF" ]; then
    echo "ERROR: File does not start with PDF magic bytes"
    head -c 100 document.pdf
    exit 1
fi

Step 2: Primary Extraction (pdftotext)

# Try pdftotext first (fastest, most reliable for simple PDFs)
if command -v pdftotext &> /dev/null; then
    pdftotext -layout document.pdf output.txt 2>/dev/null
    if [ -s output.txt ]; then
        WORD_COUNT=$(wc -w < output.txt)
        if [ "$WORD_COUNT" -gt 50 ]; then
            echo "SUCCESS: pdftotext extracted $WORD_COUNT words"
            exit 0
        fi
    fi
fi

Read the full file on GitHub · 257 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. 3d ago First seen · 257 lines · 22 tokens per session scan A 8fd00e9806da

Subscribe to this mod's changes

pdf-extraction-fallbacks is a skill published in the GitHub repository HKUDS/OpenSpace (7,534 stars, last pushed 25d ago), licensed MIT. It adds 22 tokens to every session and 1,953 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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