Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-Academic-Skillsnpx agentmods add skills/alterlab-ieu/alterlab-academic-skills/alterlab-hypogenicWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-hypogenic)<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-hypogenic"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-hypogenic/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-hypogenic"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-hypogenic.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00090 | $0.03505 |
| Opus 5.5 | $0.00036 | $0.01402 |
| Sonnet 5.5 | $0.00018 | $0.00701 |
| Haiku 4.5 | $0.00009 | $0.00350 |
Grade A, and why
alterlab-hypogenic scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hypogenic
Overview
Hypogenic provides automated hypothesis generation and testing using large language models to accelerate scientific discovery. The framework supports three approaches: HypoGeniC (data-driven hypothesis generation), HypoRefine (synergistic literature and data integration), and Union methods (mechanistic combination of literature and data-driven hypotheses).
Quick Start
Get started with Hypogenic in minutes:
# Install into its own environment: hypogenic 0.3.5 pins numpy~=1.26, pandas~=2.1,
# torch~=2.4, transformers~=4.45, openai~=1.40 and anthropic~=0.32 (Python 3.10–3.12)
uv venv .venv-hypogenic --python 3.10 && source .venv-hypogenic/bin/activate
uv pip install hypogenic
# Clone example datasets
git clone https://github.com/ChicagoHAI/HypoGeniC-datasets.git ./data
# Run data-driven hypothesis generation (model_type: gpt | claude | vllm | huggingface)
hypogenic_generation --task_config_path ./data/your_task/config.yaml \
--model_type gpt --model_name <provider-model-id> \
--max_num_hypotheses 20 --output_folder ./outputs/your_task
# Run inference with a saved hypothesis bank
hypogenic_inference --task_config_path ./data/your_task/config.yaml \
--hypothesis_file ./outputs/your_task/<hypotheses_*.json> \
--model_type gpt --model_name <provider-model-id>
Flags verified against the
hypogenic0.3.5 console scripts (hypogenic_cmd). The CLI covers data-driven HypoGeniC generation and inference; HypoRefine and Union runs are driven by the example scripts (below). Run--helpfor the full option list.
Or use the example scripts (the library ships runnable scripts under examples/; there is no one-line fluent task.generate_hypotheses(...) API — see "Python API Usage" below for the real classes):
python ./examples/generation.py --help # HypoGeniC data-driven generation
python ./examples/inference.py --help # single-hypothesis inference
When to Use This Skill
Use this skill when working on:
- Generating scientific hypotheses from observational datasets
- Testing multiple competing hypotheses systematically
- Combining literature insights with empirical patterns
- Accelerating research discovery through automated hypothesis ideation
- Domains requiring hypothesis-driven analysis: deception detection, AI-generated content identification, mental health indicators, predictive modeling, or other empirical research
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · +20 lines 95b2061e163b
- 1mo ago First seen · 380 lines · 90 tokens per session scan A e8d714c4f79c
alterlab-hypogenic is a skill published in the GitHub repository AlterLab-IEU/AlterLab-Academic-Skills (78 stars, last pushed 3d ago), licensed MIT. It adds 90 tokens to every session and 3,505 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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