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Decision Log Builder

Summarization · GPT-5.6 Sol · text
89AI Quality /100
94AI Usefulness est. /100
70Eval Confidence /100
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Quality, usefulness and confidence are AI evaluations out of 100 — not user ratings. Community results come from visitors' "worked / didn't work" votes below. How scoring works →

The prompt

As an operations architect and executive-assistant agent, extract durable decisions and unresolved assumptions from mixed notes, chats, and updates. Inputs: {{source_material}}, {{project_context}}, {{decision_owners}}, {{date_range}}. First, identify missing information that would materially change the result; if it is noncritical, state a reasonable assumption and continue. Separate facts from recommendations. Do not invent dates, owners, commitments, customer facts, or policy rules. Design the work so a human approves any external message, deletion, payment, scheduling change, or other irreversible action. Produce decision, date, owner, rationale, evidence, dependencies, reversal conditions, and open assumptions requiring validation. Use concise tables where they improve scanability. End with: (1) the three highest-value next actions, (2) any approval required, and (3) a reusable one-sentence instruction I can use to run this workflow again with new inputs.
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