hypogenic
Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.
69
62%
Does it follow best practices?
Impact
74%
1.19xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/hypogenic/SKILL.mdSecurity
2 findings — 2 medium severity. This skill can be installed but you should review these findings before use.
W011: Third-party content exposure detected (indirect prompt injection risk)
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
Third-party content exposure detected (high risk: 0.90). The skill explicitly ingests untrusted third-party content — e.g., cloning public GitHub datasets and processing user/third‑party PDFs placed in literature/YOUR_TASK_NAME/raw/ (see the "git clone" commands and Literature Processing / HypoRefine steps) — and instructs the agent/LLM to read and generate/refine hypotheses from that content, which can materially influence subsequent actions.
W012: Unverifiable external dependency detected (runtime URL that controls agent)
What this means
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
Why it was flagged
Potentially malicious external URL detected (high risk: 0.90). The skill explicitly instructs runtime git clones of external repositories—e.g., https://github.com/ChicagoHAI/HypoGeniC-datasets.git and https://github.com/ChicagoHAI/Hypothesis-agent-datasets.git—whose fetched config files and prompt templates are then used by the tool (and the pip-installed package https://pypi.org/project/hypogenic/ provides code that is executed), so remote content can directly control prompts or execute code at runtime.
- Repository
- K-Dense-AI/claude-scientific-skills
- Commit
b58ad7e
- Audited
- Security analysis
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.