Vector Text Fixer
v1.0.0Fix garbled text in PDF/SVG vector graphics caused by font encoding issues, making files editable in AI tools. Supports batch processing and JSON export for...
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byAIpoch@aipoch-ai
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The name/description (repair garbled text in PDFs/SVGs) match the implementation: the script uses PyMuPDF (fitz) to parse PDFs and BeautifulSoup to parse SVGs, detects garbled text, and produces JSON/repaired outputs. Declared dependencies (bs4, fitz) are appropriate. The extra 'dataclasses' entry in requirements is unnecessary on modern Python but not harmful.
Instruction Scope
SKILL.md instructs the agent to run the included script against PDF/SVG file paths or folders and to stop when the request is out of scope. The instructions do not direct reading of unrelated system files, environment variables, or transmission of data to external endpoints. Error-handling and fallback templates constrain the behavior to repair tasks.
Install Mechanism
This is an instruction-only skill with bundled code (no install spec). It includes a requirements.txt listing PyMuPDF (fitz) and BeautifulSoup which must be installed manually or by the operator. No remote download URLs or extraction steps are present. Note: the skill will require installing packages into the Python environment where it runs.
Credentials
No environment variables, credentials, or config paths are requested. The script performs local file reads/writes only. There are no credentials or unrelated service tokens required.
Persistence & Privilege
The skill does not request persistent platform privileges (always is false) and does not modify other skills or system-wide agent settings. Autonomous invocation is allowed by default but this is the platform norm and not combined with other concerning permissions here.
Assessment
This skill appears coherent and limited to local PDF/SVG repair, but take normal precautions: (1) run it in a controlled environment (virtualenv or container) and install requirements (PyMuPDF, beautifulsoup4) before use; (2) test on copies of sensitive files before bulk processing; (3) the requirements.txt includes 'dataclasses' which is unnecessary on recent Python versions—ensure your Python version is compatible; (4) verify the script actually writes outputs in your environment (the provided code focuses on detection/suggestions and may require confirming file-write behavior); and (5) because the tool operates on local files, avoid running it on secrets you cannot expose to the machine executing the script.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.