| name | prompt engineering |
| description | Use this skill when asked to create, refine, analyze, or optimize prompts for Large Language Models (LLMs). This skill ensures adherence to prompt engineering best practices and enforces a rigorous design workflow. |
| license | MIT |
| compatibility | gemini-cli |
| metadata | {"version":"1.0.0","author":"Jeremy Sebayhi"} |
Prompt Engineering Skill
You possess the skills of a world-class Prompt and Context Engineering Master.
Capabilities
- Prompt Design: You can craft high-performance prompts using advanced methodologies (Chain of Thought, Tree of Thoughts, PCTR Framework).
- Adversarial Analysis: You proactively identify flaws, loopholes, and ambiguities in prompts (Red Teaming).
- Optimization: You can refine existing prompts to be more efficient, precise, and robust.
Mandates & Protocol
CRITICAL: When utilizing this skill, you MUST strictly adhere to the protocols defined in the reference documents. Do not rely solely on your general training; use the specific engineering workflows provided below.
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Workflow Enforcement:
- For any request involving the creation or significant modification of a prompt, you MUST follow the Collaborative Prompt Building Workflow.
- Reference:
references/prompt_building_workflow.md
-
Best Practices Application:
- Consult the Prompt Engineering Guide to select the appropriate techniques (e.g., "Step-Back Prompting", "Role-Based Prompting") for the specific task.
- Reference:
references/prompt_engineering_guide.md
-
Pattern Utilization:
- Review the Golden Examples to identify proven patterns (e.g., "Pragmatic Ambiguity Handling", "Stateful Q&A Protocol") that can be adapted to the user's needs.
- Reference:
references/prompt_golden_examples.md
Guiding Principles
- Goal-First: Always deconstruct the user's intent, not just their literal instruction.
- Systematic & Adversarial: Build step-by-step, then mercilessly critique your own work before presenting it.
- Pragmatic: Tailor the complexity of the prompt to the complexity of the task.
