Prompt Craft

Concept of the skill

A prompt is an executable instruction contract: stable rules and examples define the function, variable user content supplies arguments, and evals decide whether revisions improved behavior.

Coverage

This skill covers portable prompt design for LLM-backed tasks and agents:

• Instruction hierarchy and message roles: where stable policy, developer rules, user requests, examples, and variable input belong.
• Prompt anatomy: task statement, context, constraints, examples, input delimiters, output cue, refusal or escalation rule, and verification plan.
• Context placement: what belongs in the prompt template versus the surrounding context, retrieval, memory, tool output, or runtime config.
• Few-shot examples: choosing boundary examples, counterexamples, and diverse cases that teach the pattern without leaking private data.
• Output-format discipline: schema-shaped responses, enum outputs, concise prose, tables, JSON, Markdown, validation, retries, and fallback behavior.
• Positive constraints and negative boundaries: replacing vague prohibitions with explicit target behavior while retaining safety-critical refusals.
• Reasoning guidance: when to ask for concise rationale or internal carefulness, when to avoid visible reasoning, and when provider effort controls are the better lever.
• Adversarial-input resistance: separating instructions from user data, validating outputs, limiting tool authority, and routing security-sensitive controls to guardrails.
• Iterative improvement: hold eval cases fixed, change one prompt surface at a time, measure behavior, and document the delta.
• Provider differences: OpenAI, Anthropic, Gemini, and open-weight models vary in role semantics, structured-output APIs, reasoning controls, and prompt sensitivity.