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 phanghonghao/THU-Awesome-Skills --skill pdf-readergit clone --depth 1 https://github.com/phanghonghao/THU-Awesome-SkillsWrote 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/phanghonghao/thu-awesome-skills/pdf-reader)<a href="https://agentmods.dev/skills/phanghonghao/thu-awesome-skills/pdf-reader"><img src="https://agentmods.dev/badge/skills/phanghonghao/thu-awesome-skills/pdf-reader/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/phanghonghao/thu-awesome-skills/pdf-reader"><img src="https://agentmods.dev/badge/skills/phanghonghao/thu-awesome-skills/pdf-reader.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00085 | $0.02454 |
| Opus 5.5 | $0.00034 | $0.00982 |
| Sonnet 5.5 | $0.00017 | $0.00491 |
| Haiku 4.5 | $0.00009 | $0.00245 |
Grade A, and why
pdf-reader 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 2mo 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 — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Reader Skill (PyMuPDF)
Use PyMuPDF (import fitz) to read PDF files. Supports 3 extraction modes with increasing fidelity. Handles Chinese text, multi-page PDFs, and image-based PDFs.
When to Use
- Any time you need to read a .pdf file — always use this instead of the native Read tool
- User mentions: "read PDF", "读取PDF", "PDF内容", "提取PDF", "PDF text", "open PDF"
- User provides a file path ending in
.pdf - Any task requiring PDF content extraction
Extraction Modes
Choose the mode based on the downstream task:
| Mode | Method | Output | Best for |
|---|---|---|---|
| text (default) | get_text() |
Plain text | Simple reading, summarization |
| html | get_text("html") |
HTML with CSS formatting | High-fidelity intermediate format, preserving bold/italic/font size/color |
| dict | get_text("dict") |
Structured JSON-like dict | Maximum fidelity — font name, size, color, position, flags; ideal for PDF → .tex conversion |
Mode selection guide:
- Just need to read content? →
text - Need to preserve formatting (bold, italic, headings, tables)? →
html - Converting PDF to .tex/.docx and need font size / layout info? →
dict - Not sure? → Use
dict(most complete, can derive everything else)
Implementation
Step 1: Check PyMuPDF Installation
python -m pip install PyMuPDF 2>&1 | tail -3
Step 2: Extract PDF Content
Always set PYTHONIOENCODING=utf-8 to avoid GBK encoding issues on Windows.
Mode: text (default — plain text extraction)
PYTHONIOENCODING=utf-8 python -c "
import fitz, sys
pdf_path = sys.argv[1]
doc = fitz.open(pdf_path)
print(f'Total pages: {len(doc)}')
for page in doc:
text = page.get_text()
if text.strip():
print(f'--- Page {page.number + 1} ---')
print(text)
else:
print(f'--- Page {page.number + 1}: [empty/image-only] ---')
doc.close()
" "<PDF_PATH>"
With page range:
PYTHONIOENCODING=utf-8 python -c "
import fitz, sys
pdf_path = sys.argv[1]
start, end = int(sys.argv[2]) - 1, int(sys.argv[3])
doc = fitz.open(pdf_path)
print(f'Total pages: {len(doc)}, extracting pages {start+1}-{end}')
for i in range(start, min(end, len(doc))):
text = doc[i].get_text()
if text.strip():
print(f'--- Page {i + 1} ---')
print(text)
else:
print(f'--- Page {i + 1}: [empty/image-only] ---')
doc.close()
" "<PDF_PATH>" "<START>" "<END>"
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.
- 2mo ago First seen · 230 lines · 85 tokens per session scan A cbfbc5d4db7c
pdf-reader is a skill published in the GitHub repository phanghonghao/THU-Awesome-Skills (8 stars, last pushed 3mo ago), licensed MIT. It adds 85 tokens to every session and 2,454 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
pdf-reader compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| pdf-readerphanghonghao/THU-Awesome-Skills | Skill | 8 | 3mo ago | MIT | A | 85 | Claude Code, Codex |
| apify-youtube-transcript-scrapersickn33/agentic-awesome-skills | Skill | 49k | yesterday | MIT | A | 48 | Claude Code |
| foundry-hosted-agent-validationmicrosoft/agent-framework | Skill | 15k | yesterday | MIT | A | 82 | Claude Code, Codex |
| report-to-pdfasgeirtj/system_prompts_leaks | Skill | 71k | yesterday | CC0-1.0 | A | 17 | Claude Code, Codex |
| pdf-extract-create-workflowHKUDS/OpenSpace | Skill | 7.9k | yesterday | MIT | A | 22 | Claude Code, Codex |
| document-direct-pythonHKUDS/OpenSpace | Skill | 7.9k | yesterday | MIT | A | 20 | Claude Code, Codex |
| pdf-verification-cliHKUDS/OpenSpace | Skill | 7.9k | yesterday | MIT | A | 19 | Claude Code, Codex |