alterlab-hypogenic
From the author
Runs automated LLM-driven hypothesis generation and testing on tabular datasets with HypoGeniC, combining literature insights with data-driven testing. Use when systematically exploring hypotheses about patterns in empirical data (for example deception detection or content analysis). For manual hypothesis formulation use alterlab-hypothesis-gen; for open-ended creative ideation use alterlab-scientific-brainstorm. Part of the AlterLab Academic Skills suite.
Install
npx skills add AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-hypogenic -a claude-code
Installs to .claude/skills/alterlab-hypogenic/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
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Similar skills
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- hypogenicK-Dense-AI/scientific-agent-skillsPlans and audits use of ChicagoHAI HypoGeniC/HypoRefine for LLM-assisted hypothesis generation from labeled text datasets. Use for the `hypogenic` package, its task configs, hypothesis banks, or HypoBench datasets—not for manual hypothesis formulation or scientific validation.Science★ 54.4K
- hypogenic-hypothesis-generationjaechang-hits/SciAgent-SkillsLLM-driven hypothesis generation/testing on tabular data. Three methods: HypoGeniC (data-driven), HypoRefine (literature+data), Union. Iterative refinement, Redis caching, multi-hypothesis inference. Manual: hypothesis-generation; ideation: scientific-brainstorming.Testing★ 382
- alterlab-hypothesis-genAlterLab-IEU/AlterLab-Academic-SkillsFormulates structured, testable hypotheses from experimental observations using a scientific-method framework — derives predictions, proposes mechanisms, and designs experiments to test them, then renders a LaTeX report. Use when turning observations or data into falsifiable, mechanistic hypotheses, competing-explanation sets, testable predictions, or experimental designs. For a standalone systematic literature review or evidence synthesis (not a means to hypotheses) use alterlab-literature-review; for open-ended brainstorming before any specific observation use alterlab-scientific-brainstorm; to evaluate an existing manuscript use alterlab-peer-review. Part of the AlterLab Academic Skills suite.Testing★ 78
- alterlab-scientific-brainstormAlterLab-IEU/AlterLab-Academic-SkillsCreative research ideation and exploration for open-ended brainstorming, surfacing interdisciplinary connections, challenging assumptions, and identifying research gaps. Use when starting early-stage research planning with no specific observations yet — for open-ended brainstorming sessions, exploring cross-disciplinary connections, or finding gaps. For formulating testable hypotheses from observations or data use alterlab-hypothesis-gen; for grading evidence or spotting design flaws use alterlab-scientific-thinking. Part of the AlterLab Academic Skills suite.Science★ 78
- hypothesis-generationforyourhealth111-pixel/Vibe-SkillsStructured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Also owns explicit HypoGeniC-style or automated LLM-driven hypothesis generation/testing requests inside this single skill. For open-ended ideation use scientific-brainstorming.Testing★ 3.8K
- alterlab-statsmodelsAlterLab-IEU/AlterLab-Academic-SkillsStatistical modeling in Python with statsmodels — OLS/WLS/GLS, GLM, discrete-choice and count models, mixed models, ARIMA/SARIMAX/VAR, with diagnostics, robust standard errors, and coefficient-level inference. Use when fitting specific model classes for econometrics, time series, or rigorous inference with coefficient tables and confidence intervals, or when updating code for statsmodels 0.15 (result_object named results, rng keyword). For guided statistical test selection with APA reporting prefer alterlab-statistical-analysis. Part of the AlterLab Academic Skills suite.Testing★ 78
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