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world-cup-predictor【开发与工程】Predict FIFA World Cup matches, full tournament paths, and champion probabilities through Codex-native subagents that analyze live news, weather, injuries, markets, Polymarket, tactics, and tournament context while updating a real-time web dashboard. Use when asked to forecast World Cup games, predict the full World Cup outlook, compare match forecas…
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Use this skill to run an agent-native World Cup prediction room. The invoking Codex agent starts the web dashboard first, collects current signals, spawns subagents for independent analysis, and publishes each prediction update to the page as subagent results arrive.
Do not substitute deterministic, static, or hardcoded forecasts. The model reasoning must come from the current Codex agent and its subagents.
For broad requests such as "predict this World Cup", "predict the tournament path", "who will win", or "预测这一届世界杯走向":
python3 scripts/start_dashboard.py --port 8789 from the skill root in a long-running foreground tool session.&; some Codex shells clean up detached processes before the browser can connect.scripts/bootstrap_worldcup.py --out assets/dashboard/data.scripts/set_live_state.py --stage kickoff --message "Starting subagent World Cup prediction room" --progress 0.03.assets/dashboard/data/locked-results.json with scripts/sync_locked_results.py.scripts/collect_signals.py --out assets/dashboard/data/signals.json.signals.json contains Polymarket rows with status: "fallback-required" or odds with status: "missing ODDS_API_KEY", preserve those rows and have the market subagent manually inspect the listed public pages. Do not treat empty market data as zero probability.scripts/set_live_state.py --stage signal-collection --message "Collected news, markets, weather, and optional odds" --progress 0.10.references/agent-native-workflow.md, references/research-protocol.md, and references/dashboard-data-contract.json.references/agent-native-workflow.md.
markets and news-weather as sidecar signal agents.group-a through group-l).scripts/publish_dashboard.py.
scripts/publish_dashboard.py --complete.After publishing final dashboard data, run the local regression suite:
python3 -m unittest discover -s tests -v
If invoking from the repository root instead of the skill root, use:
python3 -m unittest discover -s world-cup-predictor/tests -v
These tests use Python's standard unittest framework. Do not require pytest unless a future dependency file explicitly adds it. Treat missing pytest as an environment/tooling issue, not a failed regression.
assets/dashboard/data/live-state.json and assets/dashboard/data/predictions.json.assets/dashboard/data/replay.json; preserve it through the run so the completed dashboard can replay the forecast room.references/dashboard-data-contract.json.signals.json and state the connector failure in the dashboard narrative.references/agent-native-workflow.md: default no-key workflow for Codex agents that spawn subagents.references/research-protocol.md: source checklist, probability calibration, and confidence rubric.references/subagents.md: role prompts and handoff contracts for subagents.references/prediction-schema.json: JSON contract for match-level agent outputs.references/dashboard-data-contract.json: JSON contract for dashboard-level tournament predictions.references/worldcup-2026-groups.json: bootstrap group snapshot.scripts/bootstrap_worldcup.py: create dashboard data scaffolding.scripts/start_dashboard.py: start the static dashboard on 8789 or the next free port.scripts/collect_signals.py: collect current news RSS, Polymarket, weather, and optional odds signals.scripts/set_live_state.py: update the dashboard broadcast strip.scripts/replay_history.py: append dashboard snapshots for post-run replay.scripts/sync_locked_results.py: maintain already-finished match results that should not be predicted.scripts/publish_dashboard.py: publish partial or final subagent-derived dashboard predictions.scripts/merge_predictions.py: merge role-specific match packets when subagents produce overlapping outputs.scripts/validate_skill.sh: create a local virtualenv, install validation dependencies, and run the official skill validator.assets/dashboard/: static live dashboard.