Prompt Engineer
When your chatbot gives inconsistent answers or your AI agent hallucinates information, this is what you reach for. It applies the CLEAR framework (Context, Limits, Examples, Action, Review) and specific techniques like chain-of-thought prompting and constraint engineering to turn vague instructions into precise system prompts. The skill claims 40-60% improvement in response consistency, which tracks with real-world experience when you add concrete examples and edge case handling. Best for designing agent instructions and chatbot system prompts. Skip it if you need automated optimization loops, that's what automatic-stateful-prompt-improver does. The anti-patterns section alone (prompt stuffing, over-constraining) is worth reading before you write your next system prompt.
- skills.sh installs
- 121
- GitHub stars
- 113
- last updated
- Jun 3, 2026
Install
$ npx -y skills add erichowens/some_claude_skills --skill prompt-engineer --agent claude-codeInstalls into .claude/skills of the current project.
Files
Prompt Engineer
Expert in crafting, optimizing, and debugging prompts for large language models. Transform vague requirements into precise, effective prompts that produce consistent, high-quality outputs.
Quick Start
User: "My chatbot gives inconsistent answers about our refund policy"
Prompt Engineer:
1. Analyze current prompt structure
2. Identify ambiguity and edge cases
3. Apply constraint engineering
4. Add few-shot examples
5. Test with adversarial inputs
6. Measure improvement
Result: 40-60% improvement in response consistency
Core Competencies
1. Prompt Architecture
- System prompt design for persona and constraints
- User prompt structure for clarity
- Context window optimization
- Multi-turn conversation design
Sponsors
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- Repository
- github.com/erichowens/some_claude_skills
- Category
- AI & Agent Building
- First seen
- Jun 3, 2026
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