| name | prompt-engineering |
| description | Create, update, review, or discuss an LLM prompt — system prompt, skill, or agent. State the goal, trust the model, add only what closes a real gap in natural behavior. Use when writing or improving prompts, discussing a skill or agent, diagnosing prompt failures, or when the user says a prompt needs work. |
| argument-hint | <request> |
| user-invocable | true |
A prompt earns its place where natural model behavior misses what's needed. State the goal and the expected outcome; trust the model for everything else. Lines belong only when they close a real gap — observed gotchas, non-obvious behavior, knowledge the model doesn't have, or edge cases it gets wrong by default. Each line must also hold at the edges of where the prompt runs: name principles and portable capabilities in natural language, not harness-bound primitives; scope rules to the principle's natural reach, not narrower; unify split restatements of the same rule. Length follows the gap, not a number. On update, calibrate both directions: add what closes the new gap, and prune what no longer earns its place. A prompt stays in balance over time; it doesn't accrete.
Branch on intent. Creating: discover the goal, audience, and the specific gap; draft the minimum that closes it. Updating: find each existing line's gap before changing anything around it — patches that replace often beat patches that add. Reviewing: of each line ask both "would the model do this without it?" and "does this hold at the edges?" — flag the no's. Diagnosing a failing prompt: see — find the line driving the symptom before patching.
