anthropic-1p-prompt-optimizer

Optimize, rewrite, and evaluate prompts using the Anthropic 1P interactive prompt-engineering tutorial patterns (clear/direct instructions, role prompting, XML-tag separation, output formatting + prefilling, step-by-step “precognition”, few-shot examples, hallucination reduction, complex prompt templates, prompt chaining, and tool-use XML formats). Use for 提示词优化/Prompt优化/Prompt engineering, rewriting system+user prompts, enforcing structured outputs (XML/JSON), reducing hallucinations, building multi-step prompt templates, adding few-shot examples, or designing prompt-chaining/tool-calling scaffolds.

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Install skill "anthropic-1p-prompt-optimizer" with this command: npx skills add rexleimo/rex-skills/rexleimo-rex-skills-anthropic-1p-prompt-optimizer

Anthropic 1p Prompt Optimizer

Overview

Turn vague “帮我改一下提示词/Make this prompt better” into a repeatable workflow:

  1. clarify goals + constraints, 2) restructure the prompt using proven building blocks, 3) add formatting/examples/guardrails, 4) propose a small test plan for iteration.

Workflow (1P-style)

Step 0: Intake (ask only what’s missing)

Request:

  • Current prompt (system + user), and where it runs (UI / API / multi-turn).
  • Target behavior: success criteria + non-goals.
  • Inputs the prompt will receive (and typical edge cases).
  • Required output format (plain text / XML / JSON) + strictness.
  • Common failures (hallucination, wrong tone, ignored constraints, formatting drift).

Step 1: Diagnose quickly

Check for:

  • Ambiguous verbs (e.g., “analyze”, “optimize”) without definitions.
  • Missing role/audience/tone context.
  • Data mixed with instructions (needs XML delimiting).
  • Output format underspecified (needs tags / JSON schema / prefilling).
  • No examples for tricky formatting or edge cases.

Step 2: Apply building blocks (pick only what helps)

Preferred building blocks from the tutorial (details in references):

  • Clear + direct instructions; explicitly ask for what you want.
  • Role prompting (optionally include intended audience).
  • Separate variable input from instructions using XML tags.
  • Enforce output format via XML/JSON + optional prefilling (“speaking for Claude”).
  • Add “precognition” for multi-step reasoning (thinking step-by-step).
  • Use few-shot examples to lock tone and formatting.
  • Reduce hallucinations with “give an out” + evidence-first extraction.
  • For complex prompts, use the 1P complex-prompt element ordering.

Step 3: Ship revisions as artifacts

Always output:

  • Revised system prompt (if needed) and revised user prompt.
  • Any few-shot examples and XML tag wrappers.
  • A short change log (what changed and why; 5–10 bullets max).
  • 3–5 test cases with pass/fail criteria.

Reference Files (load as needed)

  • references/anthropic-1p-cheatsheet.md: chapter-by-chapter patterns and “why it works”.
  • references/complex-prompt-template.md: the 1P complex prompt element list + skeleton.
  • references/guardrails-hallucinations.md: “out”, evidence-first, placement, temperature tips.
  • references/tool-use-xml.md: function-calling XML formats (<function_calls>, <function_results>).
  • references/iteration-checklist.md: prompt chaining + evaluation loop.

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