Pandas
v1.0.1Analyze, transform, and clean DataFrames with efficient patterns for filtering, grouping, merging, and pivoting.
⭐ 0· 1.1k·17 current·17 all-time
byIván@ivangdavila
MIT-0
Download zip
LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description (Pandas helper) align with requirements and instructions. Requesting python3 is expected and there are no unrelated binaries, env vars, or config paths.
Instruction Scope
SKILL.md focuses on local DataFrame operations and storing preferences in ~/pandas/memory.md. This is coherent, but the skill reads/writes a folder in the user's home and the working directory — users should be aware preferences and any saved snippets live on disk. The instructions assert 'no external upload' and 'no access outside ~/pandas/ and the working directory'; those are behavioral constraints in prose (not technically enforced), so trust is required.
Install Mechanism
No install spec or downloaded code — instruction-only skills write nothing beyond the documented ~/pandas/ memory files. This is low-risk compared with bundles that fetch remote binaries.
Credentials
The skill requests no credentials, env vars, or config paths. That is proportionate for a local pandas helper.
Persistence & Privilege
always is false and the skill stores only its own memory under ~/pandas/. It does not request persistent system-wide privileges or modify other skills. Autonomous invocation is allowed (platform default) but not a red flag here.
Assessment
This skill appears coherent and low-risk: it is an instruction-only pandas helper that will create and read ~/pandas/memory.md and optional snippets. Before installing, consider: (1) Are you comfortable with a small preferences file being created in your home directory? Review its contents if you store sensitive context. (2) Ensure python3 is available on the system. (3) Although the skill says it won't send data externally, this is a behavioral claim in text — avoid using sensitive secrets or production credentials in example data unless you verify the agent environment's network restrictions. (4) If you want extra isolation, run the skill under a separate user account or in a sandboxed environment. Overall, the skill is internally consistent with its stated purpose.Like a lobster shell, security has layers — review code before you run it.
latestvk9743dv9p81etxcychj896a0fd81t2gs
License
MIT-0
Free to use, modify, and redistribute. No attribution required.
Runtime requirements
🐼 Clawdis
OSLinux · macOS · Windows
Binspython3