reliable-pdf-extraction

reliable-pdf-extraction is a skill for Claude Code, Codex from HKUDS/OpenSpace. It costs 23 tokens per session (661 once invoked), scanned A, original, MIT.

A workflow for extracting text and tables from PDF files when ordinary file reading fails. It recommends command-line tools and Python libraries for different PDF layouts.

In plain words
What is it for?
Extracting PDF text, preserving its layout, inspecting metadata, and reading tables.
Why use it?
It helps recover usable text from PDFs that return errors, images, or badly structured output.

Skill for Claude CodeCodex

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

Good fit Extracting PDF text, preserving its layout, inspecting metadata, and reading tables.

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Install with agentmods
npx agentmods add skills/hkuds/openspace/reliable-pdf-extraction
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 reliable-pdf-extraction
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 reliable-pdf-extraction

README.md
[![agentmods](https://agentmods.dev/badge/skills/hkuds/openspace/reliable-pdf-extraction.svg)](https://agentmods.dev/skills/hkuds/openspace/reliable-pdf-extraction)
Your own site
<a href="https://agentmods.dev/skills/hkuds/openspace/reliable-pdf-extraction"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/reliable-pdf-extraction.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 661 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 $0.00661
Opus 5 $0.00012 $0.00331
Sonnet 5 $0.00005 $0.00132
Haiku 4.5 $0.00002 $0.00066

Measured 4d ago against content hash 6763808cb5cd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

reliable-pdf-extraction 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/reliable-pdf-extraction/SKILL.md · 102 lines

How it starts

The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Reliable PDF Text Extraction

Problem

The read_file tool with filetype='pdf' often returns binary image data, errors, or unusable output when attempting to extract text from PDF documents. This makes it unreliable for structured data extraction tasks.

Solution

Use run_shell with command-line tools (pdftotext, pdfinfo) or execute_code_sandbox with Python libraries (PyMuPDF, pdfplumber) to extract PDF text content reliably.

Methods

Method 1: pdftotext (Recommended for simple extraction)

# Extract all text to stdout
pdftotext input.pdf -

# Or extract to file
pdftotext input.pdf output.txt
cat output.txt

Method 2: pdfinfo (For metadata)

pdfinfo input.pdf

Method 3: Python with PyMuPDF (fitz)

import fitz  # PyMuPDF

doc = fitz.open("input.pdf")
text = ""
for page in doc:
    text += page.get_text()
print(text)
doc.close()

Method 4: Python with pdfplumber (Better for tables/structured data)

import pdfplumber

with pdfplumber.open("input.pdf") as pdf:
    for page in pdf.pages:
        text = page.extract_text()
        print(text)
        # For tables:
        # tables = page.extract_tables()

Workflow

  1. Attempt read_file with filetype='pdf' first (in case it works)

  2. Check output - If you receive:

    • Binary/garbage data
    • Error messages
    • Empty or truncated content
    • Image data instead of text
  3. Fall back to one of the extraction methods above:

    • Use pdftotext via run_shell for quick text extraction
    • Use pdfplumber via execute_code_sandbox for structured data/tables
    • Use PyMuPDF for complex layouts or when you need more control
  4. Process the extracted text for your task

Example Usage

# Via run_shell
result = run_shell(command="pdftotext document.pdf -")
pdf_text = result.stdout

# Via execute_code_sandbox
code = """
import pdfplumber
with pdfplumber.open("/path/to/document.pdf") as pdf:
    for page in pdf.pages:
        print(page.extract_text())
"""
result = execute_code_sandbox(code=code)
pdf_text = result.stdout

Read the full file on GitHub · 102 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 · 102 lines · 23 tokens per session scan A 6763808cb5cd

Subscribe to this mod's changes

reliable-pdf-extraction is a skill published in the GitHub repository HKUDS/OpenSpace (7,534 stars, last pushed 26d ago), licensed MIT. It adds 23 tokens to every session and 661 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.

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