{
  "name": "biostat-agent",
  "owner": {
    "name": "Ahmad Sofi-Mahmudi",
    "email": "choxos@users.noreply.github.com",
    "url": "https://github.com/choxos"
  },
  "metadata": {
    "description": "Comprehensive biostatistics agent ecosystem for R with 30 specialized agents, 17 workflow commands, and 45 methodology skills covering Bayesian modeling, indirect treatment comparisons, tidy R workflows, and clinical trial simulations",
    "version": "1.0.0"
  },
  "plugins": [
    {
      "name": "bayesian-modeling",
      "source": "./plugins/bayesian-modeling",
      "description": "Create, review, and validate Bayesian models in Stan, PyMC, JAGS, and WinBUGS",
      "version": "1.1.0",
      "category": "statistics",
      "strict": false,
      "agents": [
        "./agents/model-architect.md",
        "./agents/stan-specialist.md",
        "./agents/pymc-specialist.md",
        "./agents/bugs-specialist.md",
        "./agents/model-reviewer.md",
        "./agents/test-runner.md"
      ],
      "commands": [
        "./commands/create-model.md",
        "./commands/review-model.md",
        "./commands/run-diagnostics.md"
      ],
      "skills": [
        "./skills/stan-fundamentals",
        "./skills/pymc-fundamentals",
        "./skills/bugs-fundamentals",
        "./skills/hierarchical-models",
        "./skills/regression-models",
        "./skills/time-series-models",
        "./skills/survival-models",
        "./skills/meta-analysis",
        "./skills/model-diagnostics"
      ],
      "keywords": [
        "bayesian",
        "stan",
        "pymc",
        "jags",
        "winbugs",
        "mcmc",
        "hierarchical",
        "regression",
        "time-series",
        "survival",
        "meta-analysis",
        "cmdstanr",
        "r2jags",
        "arviz",
        "python",
        "probabilistic-programming"
      ]
    },
    {
      "name": "itc-modeling",
      "source": "./plugins/itc-modeling",
      "description": "Expert agents for indirect treatment comparison modeling in R, covering pairwise MA, NMA, MAIC, STC, and ML-NMR with tidy modeling practices",
      "version": "1.0.0",
      "category": "biostatistics",
      "strict": false,
      "agents": [
        "./agents/itc-architect.md",
        "./agents/pairwise-meta-analyst.md",
        "./agents/nma-specialist.md",
        "./agents/maic-specialist.md",
        "./agents/stc-specialist.md",
        "./agents/ml-nmr-specialist.md",
        "./agents/itc-code-reviewer.md"
      ],
      "commands": [
        "./commands/itc-analysis.md",
        "./commands/itc-review.md"
      ],
      "skills": [
        "./skills/tidy-itc-workflow",
        "./skills/pairwise-ma-methodology",
        "./skills/nma-methodology",
        "./skills/maic-methodology",
        "./skills/stc-methodology",
        "./skills/ml-nmr-methodology"
      ],
      "keywords": [
        "indirect-treatment-comparison",
        "meta-analysis",
        "network-meta-analysis",
        "MAIC",
        "STC",
        "ML-NMR",
        "health-technology-assessment",
        "evidence-synthesis",
        "R",
        "biostatistics",
        "NICE-DSU",
        "tidy-modeling"
      ]
    },
    {
      "name": "r-tidy-modeling",
      "source": "./plugins/r-tidy-modeling",
      "description": "Expert agents for R data science and biostatistics covering data wrangling, feature engineering, model building, statistical evaluation, clinical trials, genomics, documentation generation, and reproducible reporting using tidyverse and tidymodels",
      "version": "1.0.0",
      "category": "data-science",
      "strict": false,
      "agents": [
        "./agents/r-data-architect.md",
        "./agents/tidymodels-engineer.md",
        "./agents/feature-engineer.md",
        "./agents/biostatistician.md",
        "./agents/data-wrangler.md",
        "./agents/viz-specialist.md",
        "./agents/reporting-engineer.md",
        "./agents/r-code-reviewer.md",
        "./agents/r-docs-architect.md",
        "./agents/r-tutorial-engineer.md"
      ],
      "commands": [
        "./commands/r-analysis.md",
        "./commands/r-code-review.md",
        "./commands/r-model-comparison.md",
        "./commands/r-clinical-analysis.md",
        "./commands/r-project-setup.md",
        "./commands/r-doc-generate.md",
        "./commands/r-tutorial-create.md"
      ],
      "skills": [
        "./skills/tidymodels-workflow",
        "./skills/tidymodels-review-patterns",
        "./skills/recipes-patterns",
        "./skills/resampling-strategies",
        "./skills/model-tuning",
        "./skills/model-evaluation",
        "./skills/survival-analysis",
        "./skills/clinical-trials",
        "./skills/bayesian-modeling",
        "./skills/epidemiology-methods",
        "./skills/genomics-analysis",
        "./skills/r-documentation-patterns",
        "./skills/roxygen2-pkgdown",
        "./skills/meta-analysis",
        "./skills/network-meta-analysis",
        "./skills/ipd-meta-analysis",
        "./skills/diagnostic-accuracy",
        "./skills/causal-mediation",
        "./skills/mendelian-randomization",
        "./skills/pharmacokinetics",
        "./skills/health-economics",
        "./skills/real-world-evidence",
        "./skills/advanced-adaptive-trials"
      ],
      "keywords": [
        "R",
        "tidyverse",
        "tidymodels",
        "data-science",
        "biostatistics",
        "clinical-trials",
        "machine-learning",
        "statistical-modeling",
        "feature-engineering",
        "reproducible-research",
        "ggplot2",
        "dplyr",
        "renv",
        "targets",
        "quarto"
      ]
    },
    {
      "name": "clinical-trial-simulation",
      "source": "./plugins/clinical-trial-simulation",
      "description": "Clinical trial simulation plugin supporting simtrial (time-to-event) and Mediana (CSE) frameworks for power analysis, sample size determination, group sequential designs, and multiplicity optimization",
      "version": "1.0.0",
      "category": "clinical-trials",
      "strict": false,
      "agents": [
        "./agents/simulation-architect.md",
        "./agents/tte-specialist.md",
        "./agents/cse-specialist.md",
        "./agents/multiplicity-expert.md",
        "./agents/gs-design-specialist.md",
        "./agents/power-optimizer.md",
        "./agents/code-reviewer.md"
      ],
      "commands": [
        "./commands/power-analysis.md",
        "./commands/sample-size.md",
        "./commands/gs-design.md",
        "./commands/multiplicity-optimization.md",
        "./commands/cse-analysis.md"
      ],
      "skills": [
        "./skills/simtrial-fundamentals",
        "./skills/mediana-fundamentals",
        "./skills/multiplicity-methods",
        "./skills/time-to-event-methods",
        "./skills/group-sequential-methods",
        "./skills/power-optimization-patterns",
        "./skills/clinical-trial-design-patterns"
      ],
      "keywords": [
        "clinical-trials",
        "simulation",
        "power-analysis",
        "sample-size",
        "survival-analysis",
        "time-to-event",
        "multiplicity",
        "group-sequential",
        "CSE",
        "simtrial",
        "Mediana"
      ]
    }
  ]
}