Scan Report
15 /100
cross-disciplinary-bridge-finder
Identifies collaboration opportunities across fields, finds experts in complementary disciplines, translates methodologies between scientific domains, and builds interdisciplinary research teams.
Legitimate cross-disciplinary research tool with no malicious behavior; minor doc-code mismatch on declared permissions but no security impact.
Safe to install
This skill is safe to use. Consider updating SKILL.md to accurately reflect that only standard Python libraries are used (no shell access or file I/O tools required).
Findings 2 items
| Severity | Finding | Location |
|---|---|---|
| Low | Permission declaration mismatch Doc Mismatch | SKILL.md:4 |
| Low | Dependencies not version-pinned Supply Chain | scripts/requirements.txt:1 |
| Resource | Declared | Inferred | Status | Evidence |
|---|---|---|---|---|
| Filesystem | WRITE | NONE | ✓ Aligned | SKILL.md:4 declares 'Write' but main.py only uses pathlib.Path for DATA_DIR crea… |
| Shell | WRITE | NONE | ✓ Aligned | SKILL.md:4 declares 'Bash' but main.py contains no subprocess, os.system, or any… |
| Network | NONE | NONE | — | No network requests found in code |
| Environment | NONE | NONE | — | No os.environ access or credential harvesting |
File Tree
5 files · 44.3 KB · 1201 lines Python 1f · 1078L
Markdown 1f · 102L
Text 2f · 11L
JSON 1f · 10L
├─
▾
scripts
│ ├─
main.py
Python
│ └─
requirements.txt
Text
├─
requirements.txt
Text
├─
SKILL.md
Markdown
└─
tile.json
JSON
Dependencies 7 items
| Package | Version | Source | Known Vulns | Notes |
|---|---|---|---|---|
networkx | >=2.8 | pip | No | Version not pinned with upper bound |
numpy | >=1.21 | pip | No | Version not pinned with upper bound |
pandas | >=1.3 | pip | No | Version not pinned with upper bound |
scikit-learn | >=1.0 | pip | No | Version not pinned with upper bound |
matplotlib | >=3.5 | pip | No | Version not pinned with upper bound |
seaborn | >=0.11 | pip | No | Version not pinned with upper bound |
openai | >=1.0 | pip | No | Imported but not actually used in code; version not pinned |
Security Positives
✓ No shell execution (no subprocess, os.system, or command injection)
✓ No network requests or data exfiltration
✓ No credential harvesting or sensitive file access (~/.ssh, ~/.aws, .env)
✓ No obfuscation techniques (no base64, eval, or anti-analysis)
✓ No reverse shell or C2 communication patterns
✓ Legitimate academic research tool with clear, understandable logic
✓ Uses well-established libraries (networkx, numpy, scikit-learn) with no custom dangerous code