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.
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.
npx skills add HKUDS/OpenSpace --skill pdf-text-extractiongit clone --depth 1 https://github.com/HKUDS/OpenSpaceWrote 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.
[](https://agentmods.dev/skills/hkuds/openspace/pdf-text-extraction)<a href="https://agentmods.dev/skills/hkuds/openspace/pdf-text-extraction"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/pdf-text-extraction.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00016 | $0.00885 |
| Opus 5 | $0.00008 | $0.00443 |
| Sonnet 5 | $0.00003 | $0.00177 |
| Haiku 4.5 | $0.00002 | $0.00089 |
Grade A, and why
pdf-text-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.
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Text Extraction (Fallback Method)
When to Use This Skill
Use this skill when read_file with filetype='pdf':
- Returns binary image data instead of text
- Produces errors or incomplete content
- Fails to extract structured data reliably
The built-in PDF handler is unreliable for structured text extraction. Shell-based tools provide more robust alternatives.
Available Methods
Method 1: pdftotext (Recommended)
# Extract text from PDF to stdout
pdftotext /path/to/file.pdf -
# Extract text to a file
pdftotext /path/to/file.pdf output.txt
# Preserve layout (maintains spacing/structure)
pdftotext -layout /path/to/file.pdf output.txt
Usage in agent:
run_shell command="pdftotext -layout /path/to/document.pdf -"
Method 2: pdfinfo (Metadata)
# Get PDF metadata (pages, author, creation date, etc.)
pdfinfo /path/to/file.pdf
Usage in agent:
run_shell command="pdfinfo /path/to/document.pdf"
Method 3: Python with PyMuPDF (fitz)
import fitz # PyMuPDF
doc = fitz.open("/path/to/file.pdf")
text = ""
for page in doc:
text += page.get_text()
doc.close()
print(text)
Usage in agent:
run_shell command="python3 -c \"import fitz; doc=fitz.open('file.pdf'); print(''.join(p.get_text() for p in doc))\""
Method 4: Python with pdfplumber (Tables)
import pdfplumber
with pdfplumber.open("/path/to/file.pdf") as pdf:
for page in pdf.pages:
text = page.extract_text()
tables = page.extract_tables() # For tabular data
Usage in agent:
run_shell command="python3 -c \"import pdfplumber; pdf=pdfplumber.open('file.pdf'); print(''.join(p.extract_text() or '' for p in pdf.pages))\""
Workflow
-
Try pdftotext first - Fastest and most reliable for plain text
run_shell command="pdftotext -layout /path/to/file.pdf -" -
If pdftotext unavailable, check for Python libraries
run_shell command="python3 -c \"import fitz; print('PyMuPDF available')\""
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.
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.
- 4d ago First seen · 133 lines · 16 tokens per session scan A d359e58c095e
pdf-text-extraction is a skill published in the GitHub repository HKUDS/OpenSpace (7,534 stars, last pushed 25d ago), licensed MIT. It adds 16 tokens to every session and 885 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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