Agent Survey Corpus
v1.0.0Download a small corpus of open-access arXiv survey/review PDFs about LLM agents and extract text for style learning. **Trigger**: agent survey corpus, ref c...
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description (download arXiv survey PDFs and extract text for style analysis) aligns with the files and code. The downloader only targets arxiv.org export API and arxiv.org/pdf URLs and writes outputs under ref/agent-surveys/, which is consistent with the stated purpose.
Instruction Scope
SKILL.md instructs editing ref/agent-surveys/arxiv_ids.txt and running scripts/run.py with workspace and max-pages options; the script reads that id list, fetches metadata, downloads PDFs and extracts the first N pages to text. The instructions do not ask the agent to read unrelated files or secrets.
Install Mechanism
There is no install spec (instruction-only install), which is low risk. However, the Python script uses third-party packages (PyMuPDF as fitz, and other tooling files reference yaml/etc.) but the skill does not declare Python dependencies or installation steps; users must install required Python packages manually before running.
Credentials
The skill requires no environment variables, no credentials, and no privileged config paths. Network access is necessary and explicitly documented; all network calls are to arxiv.org/export.arxiv.org and arxiv.org/pdf only.
Persistence & Privilege
always is false and the skill does not request persistent platform privileges. It writes files to the provided workspace only and does not modify other skills or system-level agent settings.
Assessment
This skill is coherent and limited in scope, but take these practical steps before running: 1) Run it in an explicit workspace directory (e.g., a temp folder) so PDFs/text are confined and not accidentally committed to a repo; SKILL.md notes .gitignore but verify your repo ignores ref/**/pdfs/ and ref/**/text/. 2) Ensure you install required Python packages (PyMuPDF / pymupdf and any YAML libs if you use other tooling files) — the skill does not provide an install step. 3) Confirm network access is acceptable and that downloading the listed arXiv IDs is permitted for your use case (arXiv PDFs are generally open-access but check licenses for reuse). 4) Inspect and control ref/agent-surveys/arxiv_ids.txt before running so you only download expected papers. If you want stricter isolation, run the script inside a disposable container or VM.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.
Runtime requirements
Any binpython3, python