Skill audit report
Retrieves, versions, and publishes scientific datasets with DataLad and git-annex, and captures computational provenance with datalad run, rerun, and containers-run. Use when cloning or fetching data from OpenNeuro, DANDI, datasets.datalad.org, or any DataLad dataset; when a file in a dataset reads as a broken symlink or a small pointer instead of real data; when an analysis needs a machine-readable record of how each output was produced so it can be re-executed; or when publishing a dataset to siblings such as a GitHub repository plus a storage remote. Also use to decide between DataLad and plain Git for a data-carrying repository.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
PASS100
48K GitHub stars
Stars/forks activity
PASS97
48K stars, 4.3K forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
1d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
FAIL36
command execution surface, credential or environment access
Install availability
PASS92
npx skills add K-Dense-AI/scientific-agent-skills --skill datalad
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/K-Dense-AI/scientific-agent-skills/tree/main/skills/datalad
Review status
WARN50.75
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add K-Dense-AI/scientific-agent-skills --skill datalad
Repository
88
https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/datalad
License
86
MIT
Maintenance
100
1d since push
AI review
55
Review approval is missing
README/SKILL.md completeness
86
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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Usable description available
Dependency risk
36
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
97
48K stars, 4.3K forks; issue activity unavailable in current metadata
Adoption
88
48K GitHub stars
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
Shell or command execution
highSkill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
Network access
mediumSkill likely fetches remote pages, APIs, repositories, or external services.
Filesystem access
mediumSkill may read or write project files, documents, generated artifacts, or local workspace state.
Secrets or environment access
highSkill metadata references credentials, tokens, environment variables, or secret-bearing workflows.