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Co scientist doctor

Skill panjose/Co-Scientist/skills/skills-claude-entry/co-scientist-doctor

Scientific agent skills for Claude Code and Codex that turn research goals into auditable hypothesis generation, review, ranking, evolution, and synthesis.

Install
npx -y skills add panjose/Co-Scientist --skill co-scientist-doctor

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

2.1 KB, as published. Nobody here has run it

co-scientist-doctor

Goal:

  • Run the Co-Scientist environment diagnostics and explain any failing or warning checks to the user.

Expected input:

  • no arguments for the default project-local doctor

Execution steps:

  1. Run:

    python -m tools.host.claude_project_cli doctor

    or, when machine-readable output is needed:

    python -m tools.host.claude_project_cli doctor --format json

  2. Read the emitted diagnostic output and summarize:

    • Python version health
    • Python dependency health
    • active environment / conda or virtualenv status
    • dashboard tooling (node, pnpm)
    • dashboard install/build readiness
    • project-local skill installation state
    • how budget, iteration-policy, iteration-band, stop-policy, and human-checkpoint divide responsibility
    • how dashboard ready URLs are resolved after a background bootstrap
    • what inspect_state or validation blocked means operationally

  3. If the dashboard checks warn, recommend:

    pnpm --dir apps/dashboard install
pnpm --dir apps/dashboard build

  4. If the dashboard checks pass, remind the user:

    • fresh start, run, and resume commands try a background dashboard bootstrap
    • python -m tools.host.claude_project_cli dashboard <run-dir> resolves the ready dashboard URL
    • runs/<run_id>/dashboard/LINKS.md is the human-readable dashboard receipt
    • budget controls per-round intensity, while iteration-policy controls semantic vs capped stopping
    • human-checkpoint=auto means completion-driven runs should not pause after every evolution round
    • inspect_state means review/ranking/evolution artifacts disagree and need repair before resume or overview

  5. If the project-local skills are not installed, recommend:

    powershell -File tools/install/install_co_scientist.ps1

Rules:

  • Prefer conda run -n <env> python ... over conda activate when the user is running commands through Claude Code shells.
  • Treat doctor warnings as actionable guidance, not as fatal runtime errors unless the check status is fail.

Keep looking

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