gaussian-process-mlp-hybrid
Verdict safe, but 1 finding (1 medium), mainly social engineering. Most recent scan 2026-02-05.
This skill appears to be auto-generated content that misleadingly presents a Reddit question about Gaussian Process and MLP hybrid models as a functional discussion tool for machine learning and drug discovery. The primary security concern is social engineering through deceptive descriptions - the skill claims to provide capabilities it does not actually deliver. The skill contains a non-functional placeholder script and references a missing file, further indicating it is incomplete or improperly packaged. While there are no critical security threats like data exfiltration or command injection, the misleading nature of the skill could cause users to trust it for purposes it cannot fulfill. The skill should either be removed, or completely rewritten to accurately represent its actual (minimal) functionality.
Scanner's overall assessment (LLM analyzer)
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Discussion on Gaussian Process and MLP hybrid models for uncertainty estimation. Use when exploring machine learning model architectures, uncertainty quantification, or ensemble methods for drug discovery and similar applications.
- Package
- 4 files, 4.2 KB
- SKILL.md
- 210 words, 6 sections
- Code
- Python (1)
SKILL.md covers: AI 编码 Prompt Skill · 描述 · 类型 · Prompt · 来源信息 · 元数据
Findings
MEDIUM Misleading Skill Description and Purpose Social Engineeringllm
The skill's name and description claim it provides 'Discussion on Gaussian Process and MLP hybrid models for uncertainty estimation' and suggests use for 'exploring machine learning model architectures, uncertainty quantification, or ensemble methods for drug discovery.' However, the actual content is a Reddit post asking a question about GP+MLP drawbacks, not providing any functional capability. The skill appears to be auto-generated content ('Skill generated by Clawdbot') that misleads users about its purpose and utility.
SKILL.md
Description claims 'Discussion on Gaussian Process and MLP hybrid models' but content is 'I have a feeling there must be an obvious answer here. I just came across gaussian process here...' - a question, not a discussion or tool.What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 1.8 KB |
assets/example_asset.txt | doc | 865 B |
references/api_reference.md | doc | 978 B |
scripts/example.py | script | 613 B |
External hosts referenced
www.cell.com www.reddit.com www.sciencedirect.com
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Package contents recorded 2026-10-22. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Llm analyzer. A language model reads the skill and reports intent-level issues the rules cannot express.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
- Meta analyzer. A second model pass that validates, deduplicates and re-scores the other analyzers' findings.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://clawhub.ai/skills/gaussian-process-mlp-hybrid
- Raw scan result: ai-编码-prompt-skill-scan.json
- Badge for your README:
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