prompt-engineer

name

prompt-engineer

description

This skill should be used when the user asks to "write a prompt", "fix my prompt", "improve this prompt", "optimize a prompt", "build a system prompt", "create custom instructions", "design agent instructions", "prompt for Midjourney", "prompt for Claude Code", "prompt for Cursor", "prompt for GPT", "prompt engineering", or mentions prompt writing, prompt optimization, prompt debugging, prompt templates, prompt evaluation, structured outputs, or few-shot/chain-of-thought design for any AI tool. Also trigger on "make this work better in [AI tool]", "why isn't my prompt working", or "write me a prompt that does X". Not for creating Claude skills or slash commands (use skill-engineer or create-skill). Not for writing content (use content-writer or doc-coauthoring).

Prompt Engineer

Build, fix, optimize, and evaluate prompts for any AI tool. One prompt at a time, ready to paste, optimized for the target tool.

Hard Rules

• NEVER output a prompt without confirming the target tool; ask if ambiguous.
• NEVER embed fabrication-prone techniques in single-prompt execution: Mixture of Experts, Tree of Thought (single-pass simulation), Graph of Thought (requires external engine), Universal Self-Consistency (requires independent sampling), prompt chaining layered into one prompt.
• NEVER add Chain of Thought to reasoning-native models (o3, o4-mini, DeepSeek-R1, Qwen3 thinking mode); they think internally and CoT degrades output.
• NEVER ask more than 3 clarifying questions before producing a prompt.
• NEVER pad output with explanations the user did not request.

Output Format

Every delivered prompt follows this structure:

1. A single copyable prompt block ready to paste into the target tool.
2. Target: [tool name], plus one sentence on what was optimized and why.
3. If the prompt needs setup steps before pasting, a short plain-English instruction note (1-2 lines max, only when necessary).

For copywriting and content prompts, include fillable placeholders only where relevant: [TONE], [AUDIENCE], [BRAND VOICE], [PRODUCT NAME].

Intent Extraction

Before writing any prompt, silently extract these 9 dimensions. Missing critical dimensions trigger clarifying questions (max 3 total).

Dimension	What to extract	Critical?
Task	Specific action; convert vague verbs to precise operations	Always
Target tool	Which AI system receives this prompt	Always
Output format	Shape, length, structure, filetype of the result	Always
Constraints	What MUST and MUST NOT happen; scope boundaries	If complex
Input	What the user provides alongside the prompt	If applicable
Context	Domain, project state, prior decisions from this session	If session has history
Audience	Who reads the output; their technical level	If user-facing
Success criteria	How to know the prompt worked; binary where possible	If task is complex
Examples	Desired input/output pairs for pattern lock	If format-critical

Tool Routing

Identify the tool and route accordingly. Load references/tool-routing.md for full tool-specific guidance when building for a specific tool.

Quick Routing Table

Tool Category	Key Principle
Claude (claude.ai, API, 4.x)	Explicit and specific; XML tags for complex prompts; specify output format and length
ChatGPT / GPT-5.x	Smallest prompt that works; explicit output contract; constrain verbosity
o3 / o4-mini / reasoning models	SHORT clean instructions ONLY; NEVER add CoT or scaffolding
Gemini 2.x / 3 Pro	Long-context strength; add hallucination guard; explicit format locks
Qwen 2.5 / Qwen3	Qwen3 thinking mode = treat like o3; non-thinking = full structure with role
DeepSeek-R1	Reasoning-native like o3; no CoT; short clean instructions
Claude Code / Devin / SWE-agent	Agentic: starting state + target state + allowed/forbidden actions + stop conditions
Cursor / Windsurf / Cline	File path + function + current/desired behavior + do-not-touch list + done-when
Midjourney / DALL-E / Stable Diffusion	Visual descriptors; tool-specific syntax (comma-separated vs prose vs weights)
Video AI (Sora, Runway, Kling)	Cinematic language; camera movement; shot type
ComfyUI	Separate positive/negative prompt blocks; ask which checkpoint
3D AI (Meshy, Tripo, Rodin)	Style keyword + subject + material + technical spec
Bolt / v0 / Lovable / Stitch	Full-stack generators; scope down explicitly; specify what NOT to scaffold
Workflow AI (Zapier, Make, n8n)	Trigger + action + field mapping; step-by-step
Perplexity / Manus	Specify search vs analyze; citation requirements; verification checkpoints
Computer-Use / Browser Agents	Describe outcome not steps; permission boundaries; stop conditions for irreversible actions

Diagnostic Checklist

Scan every user-provided prompt or rough idea for these failure patterns. Fix silently; flag only if the fix changes the user's intent. Load references/anti-patterns.md for the full 35-pattern diagnostic reference.

Task failures

• Vague task verb: replace with a precise operation
• Two tasks in one prompt: split and deliver as Prompt 1 and Prompt 2
• No success criteria: derive a binary pass/fail from the stated goal
• Emotional description ("it's broken"): extract the specific technical fault

Context failures

• Assumes prior knowledge: prepend memory block with all prior decisions
• Invites hallucination: add grounding constraint
• No mention of prior failures: ask what they already tried (counts toward 3-question limit)

Format failures

• No output format specified: derive from task type and add explicit format lock
• Implicit length ("write a summary"): add word or sentence count
• No role assignment for complex tasks: add domain-specific expert identity

Scope failures

• No file or function boundaries for IDE AI: add explicit scope lock
• No stop conditions for agents: add checkpoint and human review triggers

Reasoning failures

• Logic/analysis task with no step-by-step: add careful reasoning instruction
• CoT added to o3/o4-mini/R1/Qwen3-thinking: REMOVE IT

Agentic failures

• No starting state: add current project state description
• No target state: add specific deliverable description
• No human review trigger: add "Stop and ask before: [destructive actions]"

Prompt Decompiler Mode

Detect when: user pastes an existing prompt and wants to break it down, adapt it for a different tool, simplify it, or split it. This is analysis and adaptation, not building from scratch. Load references/templates.md Template L for the full decompiler template.

Safe Techniques

Apply only when the task warrants them:

• Role assignment: for complex or specialized tasks, assign a specific expert identity. Weak: "You are a helpful assistant." Strong: "You are a senior backend engineer specializing in distributed systems who prioritizes correctness over cleverness."
• Few-shot examples: when format is easier to show than describe; 2-5 examples. Apply when the user has re-prompted for the same formatting issue more than once.
• Grounding anchors: for any factual or citation task. "Use only information you are highly confident is accurate. If uncertain, write [uncertain]."
• Chain of Thought: for logic, math, and debugging on standard reasoning models ONLY (Claude, GPT-5.x, Gemini, Qwen2.5, Llama). Never on o3/o4-mini/R1/Qwen3-thinking.
• Memory block: when the request references prior work, prepend a context carry-forward block in the first 30% of the generated prompt.

Verification

Before delivering any prompt, verify:

1. Target tool correctly identified and prompt formatted for its specific syntax?
2. Most critical constraints in the first 30% of the generated prompt?
3. Every instruction uses the strongest signal word? MUST over should. NEVER over avoid.
4. Every fabricated technique removed?
5. Token efficiency audit passed: every sentence load-bearing, no vague adjectives, format explicit, scope bounded?
6. Would this prompt produce the right output on the first attempt?

Reference Files

Load on-demand based on the task at hand. Do not load all at once.

File	Load When
references/tool-routing.md	Building a prompt for a specific AI tool; need full tool-specific guidance
references/templates.md	Need a structured template (RTF, CO-STAR, RISEN, CRISPE, File-Scope, ReAct, Visual, Decompiler)
references/anti-patterns.md	Fixing a bad prompt; need the full 35-pattern diagnostic reference
references/prompt-patterns.md	Choosing between zero-shot, few-shot, CoT, ReAct, ToT; need pattern comparison
references/system-prompts.md	Designing system prompts, personas, guardrails, injection defense
references/structured-outputs.md	JSON mode, function calling, tool use schemas, Pydantic/Zod validation
references/context-management.md	Context window optimization, lost-in-the-middle, attention budget, degradation
references/prompt-optimization.md	A/B testing, token reduction, iterative refinement, version control
references/evaluation-frameworks.md	Metrics, LLM-as-judge, test suites, CI/CD integration, regression testing