meg-skill

meg-skill is a Bioinformatics & life sciences skill for AI agents, published by CUHK-AIM-Group in the NeuroClaw repository on GitHub. Skillspace rates meg-skill C (76/100) and it passed the safety scan; the rating is based on static analysis only.

Use this skill whenever the user wants to process MEG (magnetoencephalography) data including source localization, time-frequency analysis, connectivity analysis, sensor-level preprocessing, or MEG-specific feature extraction. Triggers include: 'MEG', 'MEG processing', 'MEG source localization', 'MEG connectivity', 'magnetoencephalography', 'beamformer', 'time-frequency', 'MEG preprocessing', or any request involving MEG data files (.fif, .con, .ds).

Grade
C
Quality
76 / 100
Safety
Passed
GitHub stars
74

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

View source on GitHubCUHK-AIM-Group/NeuroClaw

Our review

Architecture
91 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
MIT
Adoption
Adopted by 0 other repositories, in 2 collections

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

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