Co Scientist Run

co-scientist-run

Goal:

• Bootstrap one existing Co-Scientist run and continue with the canonical pipeline.

Expected input:

• one run directory such as runs/test1
• or one compatibility config path such as runs/test1/config.yaml

Execution steps:

1. Resolve the run directory or config path relative to the repository root.

2. Run:

   python -m tools.host.project_cli run <run-target> --skill co-scientist-pipeline
   

3. Read runs/<run_id>/state/HOST_AGENT_HANDOFF.json.

4. Read the CLI JSON result and the run-local dashboard receipt artifacts:

   • runs/<run_id>/dashboard/LINKS.md
   • runs/<run_id>/dashboard/LINKS.json

5. If the CLI JSON contains dashboardLinks:

   • If dashboard.status is running, return dashboardLinks.dashboard as the primary dashboard URL and include the deep links.
   • If dashboard.status is starting, immediately run:

   python -m tools.host.project_cli dashboard <run-dir>
   

   • Read the refreshed CLI JSON result plus runs/<run_id>/dashboard/LINKS.md.
   • If runtime.status is now running, return the refreshed links.dashboard URL as the primary dashboard URL and include the deep links.
   • If runtime.status is still starting, tell the user that the dashboard is still booting, point them to runs/<run_id>/dashboard/LINKS.md, and include the retry command:

   $co-scientist-dashboard <run-dir>
   

6. Open skills/co-scientist-pipeline/SKILL.md and the shared references listed by the handoff.

7. Continue from the canonical repository-local workflow instead of inventing a parallel flow. If the refreshed routing plan returns run_configuration, execute research-config and validate research_plan/RESEARCH_PLAN.json before any generation work.

8. After major phase writes, run:

   python -m tools.validation.contract_validation runs/<run_id> --skill co-scientist-pipeline
   

Rules:

• Use persisted artifacts as the source of truth.
• Do not skip research-config when routing requires run_configuration.
• The first active stage may be Configuration rather than Generation; do not skip it when the routing plan requires run_configuration.
• Treat skills/ as canonical and .agents/skills/ as the installed Codex discovery surface.
• Treat runs/<run_id>/dashboard/LINKS.md as the human-readable dashboard receipt and runs/<run_id>/dashboard/LINKS.json as the machine-readable receipt.
• Under completion_driven + auto, continue until the routing plan reaches overview, a configured checkpoint, or a blocking validator/safety state.
• If you must stop before convergence or a terminal route, tell the user the run is paused, current convergence has not been reached, persisted state is resumable, and the next recommended action is continue evolution through $co-scientist-resume <run-dir> or an explicit continue request.