{"id":"3e886cf8-0434-49f4-ae03-a1d4e55c4c6a","slug":"clawhub-skills-alirezarezvani-senior-prompt-engineer","name":"senior-prompt-engineer","description":"This skill should be used when the user asks to \"optimize prompts\", \"design prompt templates\", \"evaluate LLM outputs\", \"build agentic systems\", \"implement RAG\", \"create few-shot examples\", \"analyze token usage\", or \"design AI workflows\". 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Use for prompt engineering patterns, LLM evaluation frameworks, agent architectures, and structured output design.","source":"CLAWHUB","sourceId":"clawhub:skills:alirezarezvani:senior-prompt-engineer","repository":"https://github.com/openclaw/skills/tree/main/skills/alirezarezvani/senior-prompt-engineer","documentation":"https://www.xpersona.co/agent/clawhub-skills-alirezarezvani-senior-prompt-engineer","protocols":["OPENCLEW"],"languages":["typescript"],"examples":[{"kind":"example","language":"bash","snippet":"# Analyze and optimize a prompt file\npython scripts/prompt_optimizer.py prompts/my_prompt.txt --analyze\n\n# Evaluate RAG retrieval quality\npython scripts/rag_evaluator.py --contexts contexts.json --questions questions.json\n\n# Visualize agent workflow from definition\npython scripts/agent_orchestrator.py agent_config.yaml --visualize"},{"kind":"example","language":"bash","snippet":"# Analyze a prompt file\npython scripts/prompt_optimizer.py prompt.txt --analyze\n\n# Output:\n# Token count: 847\n# Estimated cost: $0.0025 (GPT-4)\n# Clarity score: 72/100\n# Issues found:\n#   - Ambiguous instruction at line 3\n#   - Missing output format specification\n#   - Redundant context (lines 12-15 repeat lines 5-8)\n# Suggestions:\n#   1. Add explicit output format: \"Respond in JSON with keys: ...\"\n#   2. Remove redundant context to save 89 tokens\n#   3. Clarify \"analyze\" -> \"list the top 3 issues with severity ratings\"\n\n# Generate optimized version\npython scripts/prompt_optimizer.py prompt.txt --optimize --output optimized.txt\n\n# Count tokens for cost estimation\npython scripts/prompt_optimizer.py prompt.txt --tokens --model gpt-4\n\n# Extract and manage few-shot examples\npython scripts/prompt_optimizer.py prompt.txt --extract-examples --output examples.json"}]}}