prompt-engineering
SolidCreate, update, review, or discuss an LLM prompt — a system prompt, a skill, or an agent. Use when writing or improving a prompt, discussing a skill or agent, diagnosing prompt failures, or when the user says a prompt needs work.
Install
Quality Score: 87/100
Skill Content
Details
- Author
- doodledood
- Repository
- doodledood/manifest-dev
- Created
- 7 months ago
- Last Updated
- 3 days ago
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
prompt-engineering
Build prompts that get accurate, reliably-shaped output from any LLM, choosing the right technique for the task. Use when writing, improving, or debugging a prompt.
prompt-engineering
Universal prompt engineering techniques for any LLM. Use when crafting, optimizing, or reviewing prompts for AI models. Triggers on requests like "improve this prompt", "write a system prompt", "optimize my instructions", "help me prompt engineer", "audit this prompt", "review my prompt", or when building agentic systems that need structured prompts.
prompt-engineering
Write, review, and optimize professional prompts for large language models. Use this skill whenever the user asks to write, draft, design, improve, fix, debug, review, or optimize a prompt, system prompt, prompt template, meta-prompt, or agent instructions; asks why a prompt "isn't working" or gives inconsistent output; asks how to prompt for a specific task (extraction, classification, generation, reasoning, tool use); or asks about prompting techniques (few-shot, chain-of-thought, XML structure, role prompting) and whether they actually work. Trigger it on casual phrasings too — "make me a prompt for X," "make this prompt better," "how should I ask the model to do Y." Assume the user may be a non-expert describing their goal in vague or lay terms; infer their intent and build the professional prompt for them, supplying the domain wording and structure they lack. Grounded in the empirical prompting literature where the evidence is strong, and honest about where guidance rests on vendor testing instead.