ThinkWithPrompt by SynotticThinkWithPrompt

Turn a busy chat channel or group export into a situation brief

A prioritized brief from raw chat logs: what happened, why it matters, what's still unknown, and what to do next.

Research & SummariesFew-ShotStandardCommunicationFill-in Template

The prompt

Turn this raw chat export into a situation brief I can act on. Source: [e.g. Slack channel, Teams thread, Telegram or WhatsApp group export] Time window covered: [DATES/TIMES] What I care about: [e.g. "the outage response", "supplier delays", "market-moving news in this sector"] Who will read the brief: [e.g. "my manager", "the on-call team"] Chat log: [PASTE] Rules: - Use only what's in the log. Separate confirmed facts from claims, rumors, and opinions, and note who said what. - Where messages conflict, show both versions instead of picking one. - Ignore chatter, jokes, and duplicates unless they change the picture. - Use times and dates from the log; don't infer ones that aren't there. Return: 1. Summary: 2-3 sentences on the current state. 2. Timeline of key events: time, what happened, source (person or message), confidence (confirmed / reported / unverified). 3. Impact: immediate and possible consequences for [WHAT I CARE ABOUT]. 4. Gaps: the critical questions the log doesn't answer, and who might know. 5. Actions: prioritized next steps, each with the reason and the risk of not acting. 6. Context (if relevant): broader trends or sentiment shifts visible in the conversation. Keep it under one page. Don't include personal details about participants beyond what's needed to attribute information.

Highlighted [brackets] are blanks to replace with your own details.

Fill in the blanks and use this promptMore Research & Summaries prompts

What to fill in

  • DATES/TIMES
  • e.g. "my manager", "the on-call team"
  • PASTE
  • WHAT I CARE ABOUT

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

Related prompts

Find more prompts like this