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strategy

Run cross-experiment competition strategy synthesis. Invokes the competition-strategist agent which loads daily_reports/* + all SESSION_NOTES.md / claudeSummary.md / submit/SUBMISSIONS.md / KAGGLE_DIRECTION.md in parallel and proposes next moves. Use weekly or at inflection points.

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Files included (1)

  • SKILL.md2.5 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Strategy Synthesis Skill

Steps

  1. Check target files exist:

    • Check KAGGLE_DIRECTION.md / claudeSummary.md / daily_reports/ / submit/SUBMISSIONS.md / workspace/
    • If any missing, mark "Not found" and pass through to agent
  2. Invoke competition-strategist agent:

    • subagent_type: competition-strategist
    • In the prompt, specify:
      • Competition name and deadline (from KAGGLE_DIRECTION.md)
      • Phase detection must be the first thing (time-based + milestone-based; warn on misalignment)
      • All subsequent proposals are restricted to that phase's "do" list (see KAGGLE_DIRECTION.md "Phase Guidance")
      • $ARGUMENTS as additional focus if given (e.g., "focus on ensemble strategy", "emphasize LB shake risk")
      • Output target: append to the "Strategy & Roadmap" section of today's daily report daily_reports/YYYYMMDD.md
  3. Append agent output to today's daily report:

    • Append to the "Strategy & Roadmap" section of today's daily report daily_reports/YYYYMMDD.md (never create a separate strategy_*.md file — records are consolidated in the daily report)
    • If today's daily report doesn't exist yet, create it via the /daily-report steps first, then append
    • Summarize key proposals (phase detection, safe+bold, unexplored, risks) for the user
    • Surface misalignment warnings first (e.g., "Entered mid phase but no working baseline")
  4. Propose next actions:

    • Pick 1-2 of the proposed next moves to recommend for tomorrow
    • Suggest /exp-new for new experiment folders or /survey-papers for further research as needed

When to Use

  • Weekly: as a regular checkpoint
  • CV plateaus: to break out of local optima
  • After LB shake: to step back and identify the cause
  • New data drop: to re-evaluate strategy
  • 1 week before deadline: to optimize remaining resource allocation

Notes

  • Agent output is fact-based. Inferences are marked "Inference:"
  • "Best X" claims must always cite source (experiment folder, daily report date)
  • Don't blindly execute agent suggestions — treat them as input for user judgment

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