promptlisted

# MasterMind — Prompt The single biggest lever on AI output quality is the prompt. Most weak results aren't a model failure — they're an **under-specified request**. This skill rewrites a user's rough ask into a prompt an AI will execute well: clear intent, only the context that matters, structured, and token-efficient. Grounded in Anthropic's prompt-engineering guidance (`~/.mastermind/engineering/core/agent-loop.md`, `product-sense.md`). ## First: get the real intent If the goal is ambiguous, **ask one or two sharp questions before rewriting** — never invent requirements the user didn't imply. You sharpen their intent; you don't hijack it. ## The rewrite checklist (apply what fits — don't bloat) 1. **Lead with the task.** State the goal in the first line, plainly. Treat the AI like a sharp new hire: say exactly what "done" looks like. 2. **Give load-bearing context only** — the *why*, the audience, the stack/constraints, what already exists. Cut backstory that doesn't change the output. 3. **Be explicit and concrete.** Replace vague adjectives ("nice", "modern", "clean") with specifics (what, for whom, which constraints, which examples to match). 4. **Structure it.** Separate the parts — `context` / `task` / `requirements` / `output format` — with headings or XML-ish tags (`<context>…</context>`) so the model can parse roles of text. 5. **Show, don't just tell.** Add one short example of the desired output (or a reference to match) when words alone are amb