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 pdftotext-fallbackgit 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/pdftotext-fallback)<a href="https://agentmods.dev/skills/hkuds/openspace/pdftotext-fallback"><img src="https://agentmods.dev/badge/skills/hkuds/openspace/pdftotext-fallback.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00025 | $0.00774 |
| Opus 5 | $0.00013 | $0.00387 |
| Sonnet 5 | $0.00005 | $0.00155 |
| Haiku 4.5 | $0.00003 | $0.00077 |
Grade A, and why
pdftotext-fallback 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.
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pdftotext Fallback for PDF Text Extraction
When to Use
Apply this pattern when:
read_fileon a PDF returns binary/image data instead of readable text- Python-based PDF extraction (PyMuPDF, pdfplumber, etc.) in
execute_code_sandboxfails or returns garbled content - You need reliable text extraction from PDF files as a recovery strategy
Why This Works
The pdftotext utility (from poppler-utils) is a mature, command-line tool that handles many PDF edge cases that confuse Python libraries or the read_file tool. It's pre-installed on most Linux systems and provides consistent, reliable text extraction.
Steps
Step 1: Detect the Failure
Recognize extraction failure when:
read_filereturns binary content, image data, or garbled text- Error messages indicate encoding issues or unsupported formats
- Python PDF libraries in sandbox fail with import errors or extraction failures
Step 2: Use pdftotext via run_shell
Extract to stdout (recommended for quick extraction):
pdftotext /path/to/file.pdf -
The - argument outputs directly to stdout for easy capture in your tool response.
Example:
run_shell("pdftotext document.pdf -")
Step 3: Handle Complex PDFs
Preserve layout (maintains original formatting):
pdftotext -layout /path/to/file.pdf -
Extract to a file (for large PDFs):
pdftotext /path/to/file.pdf /path/to/output.txt
Then read the output file with read_file.
Handle encoded text:
pdftotext -enc UTF-8 /path/to/file.pdf -
Step 4: Verify and Continue
- Check the extracted text for completeness
- If text is still garbled, the PDF may be image-based (scanned) - consider OCR tools
- Proceed with your task using the extracted text
Code Examples
Basic extraction:
# Simple text extraction
text = run_shell("pdftotext document.pdf -")
With error handling:
# Try extraction, check for success
result = run_shell("pdftotext document.pdf - && echo 'SUCCESS' || echo 'FAILED'")
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.
- 3d ago First seen · 107 lines · 25 tokens per session scan A 5d2ce16592e8
pdftotext-fallback is a skill published in the GitHub repository HKUDS/OpenSpace (7,534 stars, last pushed 25d ago), licensed MIT. It adds 25 tokens to every session and 774 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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pydicom
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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.
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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.
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.
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…