Prompting patterns

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The simple pattern

Goal: [what you want]
Context: [what Babbily should know]
Audience: [who this is for]
Constraints: [tone, length, sources, tools, files, or style]
Format: [bullets, table, memo, plan, checklist, draft, chart]

Goal: Draft a customer update.
Context: We fixed the issue and monitoring is stable.
Audience: Non-technical customer admins.
Constraints: Calm, concise, no blame, include next steps.
Format: Email draft with subject line.

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Ask for the output shape

• Return this as a table.
• Give me a 5-step checklist.
• Write this as a customer email.
• Summarize this as risks, decisions, and next steps.
• Show this as a bar chart if the data is clear enough.

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Tell Babbily what to use

• Use the attached file.
• Use web search and cite sources.
• Show me photos of the venue.
• Use Gmail to find the latest customer thread.
• Use my Memory Profile only if it helps.
• Do not use tools for this reply.

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Improve an answer with follow-ups

• Make it shorter.
• Add examples.
• Explain the trade-offs.
• Turn this into a checklist.
• Make it more customer-friendly.
• What assumptions did you make?
• What should I verify before using this?

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Prompt recipes

Draft a [format] for [audience]. The goal is [goal]. Use a [tone] tone. Include [required details]. Avoid [things to avoid].

Research [topic]. Use current public sources, cite them, and return a table with findings, source links, confidence, and open questions.

Analyze the attached file for [goal]. Return a summary, risks, important details, and recommended next actions.

Use [plugin] to find [context]. Summarize [desired result]. Ask before sending, updating, or changing anything.

Create [image or video] for [audience/use]. Style: [style]. Include [elements]. Avoid [constraints]. Shape: [square, portrait, or landscape].

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When answers miss the mark

• Restating the goal.
• Adding the audience.
• Asking for a different format.
• Providing an example of the style you want.
• Saying what to ignore.
• Starting a new thread if old context is steering the answer.
• Switching models when the task needs a different capability, or choosing Auto to let Babbily pick a model for each message.