{"id":21136,"plugin_id":"plugins_6aac006819508191a02506fb32a88714","kind":"skill","collection_source":null,"comparison_source":null,"observed_at":"2026-09-30T23:16:49.292Z","digest":"1fd2d8f14493415068880ecc7f9bc63a2f4cc447ec2ba53d268ab9a9b040ca98","against":null,"payload":{"name":"decision-consequence-ledger","description":"Map first- and second-order consequences, watch metrics and reversal signals for executive decisions. Use when the user needs decision consequence ledger for CIO decision support.","included_files":[{"relative_path":"agents/openai.yaml","size_in_bytes":143}],"skill_md_contents":"---\nname: decision-consequence-ledger\ndescription: Map first- and second-order consequences, watch metrics and reversal signals for executive decisions. Use when the user needs decision consequence ledger for CIO decision support.\n---\n\n# Decision Consequence Ledger\n\n## Mission\n\nMake downstream consequences visible before leadership commits to a decision.\n\n## Inputs\n\nAccept decision options, board notes, risk chains, project plans, finance context, architecture context, customer impact notes and missing evidence.\n\n## Workflow\n\n1. Extract decision options and implied commitments.\n2. Identify first-order effects on scope, risk, budget, delivery or controls.\n3. Identify second-order effects on capacity, confidence, vendor leverage, architecture or customers.\n4. Define watch metrics and reversal signals.\n5. Summarize what must be monitored after approval.\n\n## Output Format\n\n- Executive Summary\n- Consequence Count\n- Consequences\n- Watch Metrics\n- Reversal Signals\n- Decision Conditions\n- Evidence & Assumptions\n\n## Guardrails\n\nDo not present consequences as predictions. Mark them as decision-planning scenarios.\n"},"changes":[],"summary":"First saved snapshot. No earlier version is available for comparison.","summary_kind":"deterministic","summary_metadata":{}}