Skill audit report
Predict LC-MS/MS (MS2, tandem mass spectra) from SMILES via ICEBERG, a two-stage deep neural network. Outputs predicted m/z vs intensity spectrum, fragment ion SMILES, and a spectrum plot.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
161 GitHub stars
Stars/forks activity
WARN57
161 stars, 24 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
9d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
WARN54
command execution surface, credential or environment access
Install availability
PASS92
npx skills add learningmatter-mit/AtomisticSkills --skill chem-msms-predict
Install command safety
PASS92
standard package or runtime install path
Permission surface
FAIL22
secrets or environment access, shell or command execution
Repository evidence
PASS86
https://github.com/learningmatter-mit/AtomisticSkills/tree/main/.agents/skills/chem-msms-predict
Review status
INFO66
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add learningmatter-mit/AtomisticSkills --skill chem-msms-predict
Repository
88
https://github.com/learningmatter-mit/AtomisticSkills/tree/main/.agents/skills/chem-msms-predict
License
86
MIT
Maintenance
100
9d since push
AI review
55
The skill requires manual download of ICEBERG checkpoints from an external GitHub release, which introduces a supply-chain dependency that is not automated or verified.
README/SKILL.md completeness
86
Usable description available
Dependency risk
54
command execution surface, credential or environment access
Install command safety
92
standard package or runtime install path
Permission surface
22
secrets or environment access, shell or command execution
Stars/forks activity
57
161 stars, 24 forks; issue activity unavailable in current metadata
Adoption
68
161 GitHub stars
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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