pdf-analysis
PDF 文档解析。自动区分文字型 PDF 与扫描型 PDF，覆盖：文本/表格提取、多页全量扫描、嵌入图表 caption、单位感知数值计算。
56
62%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
Low
Low-risk findings worth noting
Fix and improve this skill with Tessl
tessl review fix ./skills/sn-da-non-spreadsheet-analysis/capability/pdf-analysis/SKILL.mdLow
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required workflow extracts readable text from a user-supplied PDF at runtime (e.g., `page.get_text("text")` for text PDFs and OCR/caption output from rendered page images via `caption.py`), so the PDF body content can be outsider-authored free text (public/attached/downloaded) that is directly ingested into the LLM context.
- Repository
- OpenSenseNova/SenseNova-Skills
- Commit
179fea1
- Audited
- Security analysis
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.