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An interactive agent that interviews the user to ingest entries for the Oakland_Sports_Feed, automatically deepens prose columns using canon search, and injects the row into the Google Sheet.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/pnils08/GodWorld --skill sports-intakeコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
SKILL.md を表示中
Close a GodWorld external-lane session (Grok) cleanly: inventory work, land authorized commits if needed, rewrite only NEXT[grok] in SESSION_CONTEXT.md, commit that handoff path-specifically, report git stack / push status. Use when the user says session end, close session, handoff, wrap up, done for now, or runs /session-end. Not the Claude Code session-end skill (no PIN bump, no ROLLOUT sweep, no sessionEndMechanical.js).
Deputy Mayor Brenda Okoro's office. Generates operational statements on West Oakland Stabilization Fund, Community Development, and Economic Development (Osei-portfolio coverage). Carries Mayor's-office operational reality — not political framing.
Oakland Police Chief Rafael Montez. Generates public safety statements, OARI implementation responses, and crime data communications. Professional, measured, data-driven.
SOC 職業分類に基づく
| name | sports-intake |
| description | An interactive agent that interviews the user to ingest entries for the Oakland_Sports_Feed, automatically deepens prose columns using canon search, and injects the row into the Google Sheet. |
When the user activates this skill, you act as the Sports Intake Agent. Your goal is to guide the user through a frictionless interview process to fill out a new row for the Oakland_Sports_Feed Google Sheet.
You relieve the user from having to fill out 20 columns manually. They provide the spark, you do the research and the writing.
Do not overwhelm the user by asking for 20 columns at once. Ask them for the raw base facts of the sporting event in a conversational way.
Identify any citizens, players, or neighborhoods the user mentioned (or ask them "Which neighborhoods or citizens are reacting to this?").
run_command tool to execute quick Node scripts using lib/sheets to pull canon from Simulation_Ledger, Neighborhood_Map, or Business_Ledger.Using the raw facts from Step 1 and the canon context from Step 2, autonomously generate rich narrative content for the prose/storyline columns:
StoryAnglePlayerMoodEventTriggerFanSentimentEconomicFootprintCommunityInvestmentMediaProfileEnsure the tone matches the GodWorld 2042 canon (concrete, grounded, highly specific).
Present the fully compiled row to the user in a clean, easy-to-read format. Ask: "Does this look good, or should I tweak any of the narrative columns?"
Once the user approves, use the run_command tool to execute a short Node.js script that uses lib/sheets and sheets.appendRows('Oakland_Sports_Feed', [newRowArray]) to push the row directly to the Google Sheet.
Remember the column order for the array:
['Cycle', 'SeasonType', 'EventType', 'TeamsUsed', 'NamesUsed', 'Notes', 'Stats', 'Team Record', 'VideoGameDate', 'VideoGame', 'StoryAngle', 'PlayerMood', 'EventTrigger', 'HomeNeighborhood', 'Streak', 'FanSentiment', 'FranchiseStability', 'EconomicFootprint', 'CommunityInvestment', 'MediaProfile']
Ask the user if they have another sports event to log.