From claude-orator
Scores prompts across 7 dimensions and restructures using 8 Anthropic techniques like XML tags and chain-of-thought. Auto-triggers on PreToolUse for unstructured subagent prompts; manual via /reprompt-orator.
How this skill is triggered — by the user, by Claude, or both
Slash command
/claude-orator:claude-oratorThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Prompt optimization. Scores prompts across 7 dimensions and restructures them using 8 Anthropic techniques. Deterministic — no LLM calls, no network, in-memory only.
Prompt optimization. Scores prompts across 7 dimensions and restructures them using 8 Anthropic techniques. Deterministic — no LLM calls, no network, in-memory only.
| Hook | When | Action |
|---|---|---|
| PreToolUse(Task) | Subagent prompt lacks structure | Suggests orator_optimize before dispatching |
Token cost: 0 on well-structured prompts (XML tags, markdown headers, action verbs). ~50-80 on vague prompts. Never blocks — suggestion only.
| Command | Description |
|---|---|
/reprompt-orator <prompt> | Optimize a prompt using Anthropic best practices |
/reprompt-orator "your prompt here" or call orator_optimize(prompt: "...")search_conversations("prompt optimization") to find past well-scored promptsorator_optimize(prompt: "...") — score and restructuresave_context(type: "decisions", ...) to preserve the optimized prompt rationaleobserve(summary: "xml-tags improved code prompts by +3.2") to track what worksorator_optimize on each under-specified promptvigil_save("before-rewrite") before applying changes| Sibling | Value | How |
|---|---|---|
| Historian | Past well-scored prompts as examples | search_conversations("prompt patterns") finds effective prompts from history |
| Praetorian | Preserve optimization rationale | Compact optimized prompts and their scores for future reference |
| Gladiator | Track what techniques work best | observe() records which techniques improve scores most |
| Oracle | Find prompt engineering tools | search("prompt patterns") discovers relevant community tools |
| Vigil | Checkpoint before batch rewrites | vigil_save() before applying optimized prompts across files |
| Tool | Purpose |
|---|---|
orator_optimize | Score prompt across 7 dimensions, apply techniques, return restructured version |
Clarity · Specificity · Structure · Context · Examples · Constraints · Tone (each 1-10)
System prompts · XML tags · Chain of thought · Few-shot · Prefill · Long context · Extended thinking · Tool use
In-memory only. Zero disk storage. No databases, no external services.
claude mcp add orator -- npx claude-orator-mcp
npx claudepluginhub vvkmnn/claude-emporium --plugin claude-oratorEvaluates prompt quality across clarity, specificity, structure, and completeness, then generates optimized versions using 58 prompting techniques like CoT, few-shot, and role-play.
Evaluates prompt quality across clarity, specificity, structure, and completeness, then generates optimized versions using 58 prompting techniques like CoT, few-shot, and role-play.
Crafts or updates LLM prompts from first principles by discovering goals, constraints, and context through targeted questions. Use for new prompts, updates, or reviews.