Double-Checking an AI-Written Summary Before Sharing It
Catch the mistakes before anyone else does
prompt.txt
Act as a practical specialist helping me with double-checking an ai-written summary before sharing it. My context: [current setup, goals, constraints].
1. List what could go wrong with this
2. Give me a short checklist to review it line by line
3. Flag the three riskiest spots to look at first
4. Suggest a final read-through routine before it goes out
Use my details, not a generic example. If a fact needed for the plan is missing, ask for it or mark the assumption. Keep the result ready to use.
#ai workflows#double-check
💡 Replace the [brackets] with your details — the more specific, the sharper the answer.
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1. Define priority tiers and exact inclusion rules.
2. Write example labels and false-positive cases.
3. Design a daily review queue and escalation path.
4. Give a five-message test set with expected labels..
Use my details, not a generic example. If a fact needed for the plan is missing, ask for it or mark the assumption. Keep the result ready to use.
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Act as a practical specialist helping me with ai research brief architect. My context: [question, decision it supports, deadline, sources allowed].
1. Break the question into falsifiable subquestions.
2. Set a source hierarchy and recency requirements.
3. Create an evidence table with claim, source, date, confidence.
4. Specify when to stop researching and how to flag gaps..
Use my details, not a generic example. If a fact needed for the plan is missing, ask for it or mark the assumption. Keep the result ready to use.
Make messy documents yield clean, auditable fields.
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1. Design a JSON schema with field types and null handling.
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4. Produce three test cases including a missing field..
Use my details, not a generic example. If a fact needed for the plan is missing, ask for it or mark the assumption. Keep the result ready to use.