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Use when converting sports evidence into probability estimates, squad recommendations, risk-adjusted rankings, or market comparisons, especially when the answer should remain explainable and uncertainty-aware in any agent runtime.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | forecasting-desk |
| description | Use when converting sports evidence into probability estimates, squad recommendations, risk-adjusted rankings, or market comparisons, especially when the answer should remain explainable and uncertainty-aware in any agent runtime. |
Use this skill when the task is to turn evidence into a forecast or ranked choice.
{
"option": "",
"probability": 0,
"confidence": 0,
"drivers": [],
"risks": [],
"change_triggers": []
}
{
"squad": [],
"captain": "",
"vice_captain": "",
"constraints_used": [],
"core_reasons": [],
"main_risks": [],
"alternatives": []
}
Use when reading, updating, or governing long-lived national-team markdown memory files so agent runs keep reusable football context without mixing stale facts, speculative claims, and append-only observations.
Use when building or extending the project's web search, crawling, scraping, parsing, or source-normalization systems for sports, fantasy, and prediction workflows, especially when reliability, provenance, freshness, and site-compliance matter across development and production runtimes.
Use when gathering football, sports, fantasy, or prediction-market intelligence from multiple sources, especially when the work requires source comparison, freshness checks, provenance tracking, and extraction of structured evidence for downstream agents in any runtime.
Use when coordinating multiple AI agents for sports, fantasy, or market-analysis tasks, especially when the work benefits from role-based decomposition, disagreement analysis, critique loops, and a final synthesized recommendation across development or production runtimes.
Use when designing or implementing the web interface for this project, especially when the goal is a trading-terminal aesthetic that still feels welcoming, readable, and simple for everyday users, and when agent outputs must be presented clearly inside the product.