A practical prompt engineering checklist for shipping work

Most prompt failures are not about “magic words.” They are missing constraints, ambiguous success criteria, or no plan for what happens when the model is wrong. Use this checklist before you paste a prompt into a pipeline or hand it to a teammate.

1. State the job in one sentence

Write the outcome first, not the vibe.

• Bad: “Help me with this email.”
• Better: “Draft a 120-word follow-up email to a prospect who missed a demo; tone: direct, no fluff; include one concrete next step.”

If you cannot state the job in one sentence, the model cannot either.

2. Separate context from instructions

Put durable context (product facts, audience, brand rules) in a labeled block. Put the task in another. Mixing them makes edits painful and invites the model to invent facts.

CONTEXT:
- Product: sudoai.net — practical AI tools for practitioners
- Audience: engineers and ops folks who dislike hype

TASK:
Write a 3-bullet changelog summary for the token estimator tool.

3. Define the output shape

Specify format, length, and forbidden patterns.

• Format: markdown / JSON / plain text / table
• Length: max words, max bullets, max code lines
• Forbid: invented citations, fake benchmarks, “As an AI…”

For structured outputs, paste a tiny schema example rather than describing it in prose.

4. Give one worked example when the task is stylistic

One good example beats five adjectives. Prefer “do it like this” over “be witty but professional but concise.”

5. Name the failure modes

Tell the model what to do when information is missing:

• “If a fact is not in CONTEXT, write UNKNOWN — do not invent.”
• “If the request conflicts with policy X, refuse and explain why in one sentence.”

6. Control temperature with process, not superstition

For extraction and formatting, keep temperature low and validate with code. For ideation, allow higher temperature but require a second pass that scores or filters ideas against hard criteria.

7. Version your prompts

Treat prompts like code:

• Name them (prompt-email-followup-v3)
• Diff them when behavior changes
• Keep a one-line “why this changed” note

Quick pre-flight (copy this)

1. Job stated in one sentence?
2. Context separated from task?
3. Output format + length specified?
4. Missing-info policy stated?
5. At least one example if style matters?
6. Prompt named and versioned?

If you need a scrubber for messy pasted prompts, use the prompt cleaner on this site. For cost awareness before you loop an agent, use the token & cost estimator.