claude

gyoshu

Scientific research automation with Python REPL, Jupyter notebooks, and multi-agent research workflows. Includes 6 agents, 2 commands, 10 tools, and 3 skills for data science and machine learning research.

243 on GitHubby Yeachan Heov0.4.33MITupdated 8 months agoproductivity
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Plugin gyoshu from marketplace gyoshu in Yeachan-Heo/My-Jogyo. Commands read from the repo's manifest — 1 month ago.

This plugin runs code on your machine — it starts local MCP servers. The exact commands are listed below; read them before installing.

What it installs

Skills (3)

  • data-analysis

    Patterns for data loading, exploration, and statistical analysis

  • experiment-design

    Best practices for designing reproducible experiments

  • ml-rigor

    Enforces baseline comparisons, cross-validation, interpretation, and leakage prevention for ML pipelines

Slash commands (2)

  • /gyoshu:gyoshu-auto

    Start goal-based autonomous research with bounded execution

  • /gyoshu:gyoshu

    Unified Gyoshu research command - start, continue, search, and manage research

Subagents (6)

  • baksa

    Adversarial PhD reviewer that challenges Jogyo's research claims and verifies evidence

  • gyoshu

    Scientific research planner - orchestrates research workflows and manages REPL lifecycle

  • jogyo-feedback

    Explores retrospective feedback to extract lessons and patterns for research improvement

  • jogyo-insight

    Gathers evidence from previous notebooks, URLs, and documentation for research support

  • jogyo-paper-writer

    Generates human-readable, narrative research reports from structured context

  • jogyo

    Scientific research agent with Python REPL and structured output markers

MCP servers (1)

  • gyoshu-mcp

    runs: /home/bellman/Workspace/My-Jogyo/src/mcp/build/index.cjs

View source on GitHub

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