Alumni Career Tracker
v1.0.0Analyze laboratory alumni career trajectories and outcomes to provide data-driven career guidance for current students and postdocs. Tracks industry vs acade...
⭐ 0· 30·0 current·0 all-time
MIT-0
Download zip
LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description match the provided code and SKILL.md: the package collects, analyzes, and visualizes alumni career data. Required files (main.py, requirements.txt, SKILL.md) and example commands align with this purpose; no unrelated services or credentials are requested.
Instruction Scope
Runtime instructions and examples focus on loading CSVs, adding/updating records, analyzing data, and producing visual reports. The examples reference reading/writing local files (CSV, JSON, PDF/HTML outputs) and running the included script, which is consistent with the stated capability. There are no instructions to read unrelated system files, environment secrets, or to POST data to external endpoints.
Install Mechanism
No install spec is provided (instruction-only install), and bundled requirements.txt lists reasonable Python packages (dataclasses, pandas, rich). No downloads from arbitrary URLs or extraction to system paths are present.
Credentials
The skill requests no environment variables, credentials, or config paths. The code operates on local files (alumni_data.json and CSV imports) and does not access external APIs or secret-bearing environment variables, so requested access is proportionate.
Persistence & Privilege
always is false and the skill does not request persistent elevated privileges. It stores its dataset in a local alumni_data.json (under the skill directory by default) and does not modify other skills or global agent settings.
Assessment
This skill appears to be what it claims: a local analytics tool that reads CSVs, stores records in a JSON file (alumni_data.json in the skill folder), and generates reports/visualizations. Before installing or running it: 1) Be aware it will store personally identifiable information (names, job titles, salary ranges, LinkedIn URLs) locally — obtain consent and follow privacy/regulatory rules (GDPR/FERPA/etc.). 2) Confirm where alumni_data.json will be written in your environment (the repository root relative to scripts/) and ensure appropriate filesystem permissions. 3) The project relies on pandas/rich; install dependencies in an isolated environment. 4) The SKILL.md allows running shell commands (Bash) to run the script; only run this in environments where executing those commands and writing local files is acceptable. If you need networked features (e.g., automatically refreshing LinkedIn data), verify and review any added code that would perform web requests or require API credentials before enabling it.Like a lobster shell, security has layers — review code before you run it.
latestvk97bftd3nywm8cgfhcp0912svs8427rg
License
MIT-0
Free to use, modify, and redistribute. No attribution required.