Why this matters
As a Prompt Engineer, you often need models to produce outputs that downstream systems can trust: clean JSON for APIs, consistent tone for brand voice, fixed bullet counts for reports, or deterministic sections for documentation. Output control and style consistency make your prompts production-safe and your results reusable.
Real tasks you will face
- Generating valid JSON for a recommender pipeline.
- Enforcing a brand voice across multiple customer emails.
- Standardizing summaries to exactly 3 bullets for a daily report.
- Ensuring no extra chatter around machine-readable output.
Concept explained simply
Output control means telling the model exactly how to format and structure its response (format, length, sections). Style consistency means keeping the same voice, tone, and wording rules across many prompts and turns.
Mental model
Think of the model as a talented writer who follows a strict template and style guide. You provide both:
- Template: the skeleton the output must follow (e.g., JSON keys, bullet counts, headings).
- Style guide: voice rules that never change (e.g., calm expert, no exclamation marks, British spelling).
When these are explicit, the model behaves predictably.
Core techniques
- State the output format explicitly (JSON/YAML/plain text; with or without code fences).
- Specify exact counts (e.g., "exactly 3 bullets") and lengths (e.g., "90–120 words").
- Freeze voice with a named style guide block and refer to it each turn.
- Ban extraneous text (e.g., "No explanations. Output only the JSON object.").
- Use delimiters for inputs and schemas to avoid confusion.
- Provide micro-examples when format is tricky.
Worked examples
Example 1 — Valid JSON with fixed keys
Prompt:
System: STYLE_GUIDE - Voice: concise, neutral, no emojis. - Formatting: JSON only, no code fences, no explanations. User: Using the STYLE_GUIDE, return an object with keys: "headline" (string), "tags" (array of exactly 3 lowercase strings), "tone" (string set to "upbeat"). Topic: Weekend city break tips for Paris Output only the JSON object.
Expected pattern:
{
"headline": "...",
"tags": ["...", "...", "..."],
"tone": "upbeat"
}Example 2 — Fixed bullet count and tense
Prompt:
Summarize the text between <doc> tags as exactly 3 bullet points. - Style: empathetic, present tense, plain language. - Each bullet: max 14 words. - Output: bullets only, no intro/outro. <doc>Customer reports long wait times and unclear refund steps ...</doc>
Expected pattern:
- Acknowledge frustration and validate the experience. - Explain current refund steps in simple order. - Offer direct contact path for immediate help.
Example 3 — Brand voice rewrite with length control
Prompt:
Rewrite the message in the BRAND_VOICE. BRAND_VOICE: - Persona: calm expert - Tone: confident, never hype - Rules: British spelling, no exclamation marks, avoid "cutting-edge" - Length: 80–100 words Message: "Our AI totally revolutionises workflows and is insanely fast! Get started now!!!"
Expected pattern: A 80–100 word paragraph in British English, calm, confident, without hype words or exclamation marks.
Patterns you can reuse
- Output-only gate: "Output only the [FORMAT]. No commentary, no code fences."
- Exact-count rule: "Return exactly N items, numbered 1–N, one sentence each."
- Schema-first JSON: "Return a JSON object with keys A, B, C only; use double quotes; arrays for lists; values must be strings unless noted."
- Named style guide: "You are STYLE_GUIDE. Adhere to it in every response."
- Section headers: "Produce sections: Overview, Risks, Next Steps. Each 2 sentences."
- Safe refusals: "If constraints conflict, state 'CONSTRAINT_CONFLICT' only."
Exercises
Do these to lock in the skill. The quick test is at the end. Note: Anyone can take the test; only logged-in users will have their progress saved.
Exercise 1 — Strict JSON plan
Create a prompt that forces an LLM to output a four-field JSON object for the given task. Constraints:
- Keys: "user_goal" (string), "steps" (array of exactly 3 short strings), "risks" (array of exactly 2 short strings), "style_tag" (string set to "concise").
- Output: JSON only, no code fences, no extra text.
- Task topic: Plan a 20‑minute home workout with no equipment.
Checklist
- Specifies keys and allowed values clearly.
- Specifies exact list counts.
- Bans explanations and code fences.
- Uses input delimiters if needed.
Sample solution idea
System: You are precise. Output only valid JSON, no code fences, no commentary. User: Return a JSON object with keys and constraints: - user_goal: a short string. - steps: array of exactly 3 short, actionable strings. - risks: array of exactly 2 short strings. - style_tag: the string "concise". Topic: Plan a 20-minute home workout with no equipment.
Exercise 2 — Consistent support email
Write a prompt that generates a customer support apology email with these constraints:
- Word count: 90–120 words.
- Tone: friendly, non-defensive, ownership language.
- Structure: 3 bullet points detailing concrete fixes, then a single closing sentence with a direct support path.
- Banned: exclamation marks, emojis.
Checklist
- Defines tone and banned items.
- Specifies word range and structure.
- States output rules clearly.
Sample solution idea
System: STYLE_GUIDE - Tone: friendly, accountable, no exclamation marks/emojis. - Length: 90–120 words. - Structure: greeting, brief apology sentence, 3 bullets of fixes, closing sentence with contact path. User: Write the email about delayed shipping orders. Output the email only.
Common mistakes and self-check
- Ambiguous counts: saying "a few bullets" yields variable outputs. Fix: use "exactly N".
- Mixed goals: asking for JSON and an explanation creates extra text. Fix: forbid commentary.
- Unspecified schema: missing keys or wrong casing. Fix: list keys and case precisely.
- Voice drift across turns: relying on memory. Fix: include a named STYLE_GUIDE and reference it.
- Impossible constraints: conflicting rules (e.g., 50 words but 10 sections). Fix: add a conflict rule or adjust scope.
Self-check prompts
- Does the prompt ban or allow commentary explicitly?
- Are counts and lengths testable?
- Can a teammate reproduce the output without guessing?
- Is the style guide portable to the next prompt?
Practical projects
- API-ready JSON summaries: Build prompts that convert bug reports to strict JSON with fixed keys; validate by parsing in your preferred language.
- Brand voice kit: Create a STYLE_GUIDE block and test it across 5 content types (tweet, email, FAQ, release notes, landing copy).
- Analytics brief generator: Prompt that always returns 4 sections (Context, Insight, Risk, Action) with exact sentence limits; run on 10 datasets’ summaries.
Learning path
- Start: Clear instructions and delimiters.
- Then: Output schemas (JSON/YAML/plain text sections).
- Next: Style guides and tone controls.
- Finally: Multi-turn consistency and validation strategies.
Who this is for
- Prompt Engineers who ship prompts into tools, pipelines, or customer-facing flows.
- Data/ML folks needing machine-readable outputs for automation.
- Writers/PMs enforcing brand tone at scale.
Prerequisites
- Basic prompt writing (roles, instructions, delimiters).
- Familiarity with JSON and arrays/strings.
- Understanding of tone/voice in writing.
Next steps
- Refactor one of your existing prompts to add strict format and a STYLE_GUIDE.
- Create a reusable snippet library for output constraints.
- Take the quick test to confirm mastery.
Mini challenge
Create a STYLE_GUIDE block for your team’s voice and a companion output template for a weekly status update. Require: 4 sections (Highlights, Risks, Blockers, Next Week), each with 2 sentences, and ban emojis. Test it on two different projects.