How do I install the Prompting skill?

Run npx skillmds@latest add diskd-ai/prompting in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Prompting safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Prompting?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Prompting free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Prompting?

diskd-ai (@diskd-ai) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Prompting by diskd-ai — Agent Skill

Name: Prompting
Author: diskd-ai

Prompting

Prompt engineering guidance for writing and improving LLM prompts. Use when asked to (1) write a prompt for a specific task, (2) review or improve an existing prompt, (3) design system prompts for AI assistants, (4) structure prompts for specific output formats (JSON, XML, markdown), or (5) apply prompt engineering techniques like few-shot, chain-of-thought, or role prompting.

diskd-ai 6908b0e 2 files · 5.2 KB Updated Sep 17, 2026

File contents

Prompt Engineering

Guide for crafting effective prompts for large language models (Claude, GPT, Gemini, Llama, etc.).

Workflow

Clarify the goal: What task should the prompt accomplish?
Choose techniques: Select from references/techniques.md
Structure the prompt: Apply appropriate format
Add constraints: Specify requirements and boundaries
Test and refine: Iterate based on outputs

Writing a New Prompt

Start with this template:

[Context/Role - optional]
[Task - required]
[Constraints/Requirements - as needed]
[Output format - as needed]
[Examples - for complex tasks]

Minimal prompt (simple tasks):

Summarize this article in 3 bullet points.

Structured prompt (complex tasks):

You are a senior code reviewer.

Review this code for:
- Security vulnerabilities
- Performance issues
- Maintainability concerns

Format your response as:
## Summary
[1-2 sentences]

## Issues
- [severity]: [description]

## Recommendations
[prioritized list]

Improving an Existing Prompt

Diagnose issues:

Problem	Solution
Output too vague	Add specific constraints or examples
Wrong format	Specify output structure explicitly
Missing details	Use chain-of-thought or decomposition
Inconsistent results	Add few-shot examples
Off-topic responses	Strengthen role/context framing

Improvement checklist:

Is the task clear and unambiguous?
Are constraints specific (not "be concise" but "under 100 words")?
Does output format match intended use?
Would examples clarify expectations?

Quick Reference: Techniques

Technique	When to Use
Few-shot	Specific format/style needed
Chain-of-thought	Complex reasoning, math, analysis
Role prompting	Domain expertise, specific tone
Task decomposition	Multi-step workflows
Constraints	Precise requirements

See references/techniques.md for detailed patterns and examples.

Quick Reference: Output Formats

Format	When to Use
XML tags	Complex prompts, clear section boundaries
JSON	Programmatic parsing, structured data
Markdown	Human-readable reports, documentation

See references/structured.md for format patterns.

System Prompts

For designing AI assistant behavior, see references/system-prompts.md.

Key sections:

Identity and role definition
Behavioral guidelines
Constraints and boundaries
Output format defaults

---name: promptingdescription: Prompt engineering guidance for writing and improving LLM prompts. Use when asked to (1) write a prompt for a specific task, (2) review or improve an existing prompt, (3) design system prompts for AI assistants, (4) structure prompts for specific output formats (JSON, XML, markdown), or (5) apply prompt engineering techniques like few-shot, chain-of-thought, or role prompting.---# Prompt EngineeringGuide for crafting effective prompts for large language models (Claude, GPT, Gemini, Llama, etc.).## Workflow1. **Clarify the goal**: What task should the prompt accomplish?2. **Choose techniques**: Select from references/techniques.md3. **Structure the prompt**: Apply appropriate format4. **Add constraints**: Specify requirements and boundaries5. **Test and refine**: Iterate based on outputs## Writing a New PromptStart with this template:```[Context/Role - optional][Task - required][Constraints/Requirements - as needed][Output format - as needed][Examples - for complex tasks]```**Minimal prompt** (simple tasks):```Summarize this article in 3 bullet points.```**Structured prompt** (complex tasks):```You are a senior code reviewer.Review this code for:- Security vulnerabilities- Performance issues- Maintainability concernsFormat your response as:## Summary[1-2 sentences]## Issues- [severity]: [description]## Recommendations[prioritized list]```## Improving an Existing PromptDiagnose issues:| Problem | Solution ||---------|----------|| Output too vague | Add specific constraints or examples || Wrong format | Specify output structure explicitly || Missing details | Use chain-of-thought or decomposition || Inconsistent results | Add few-shot examples || Off-topic responses | Strengthen role/context framing |**Improvement checklist**:- Is the task clear and unambiguous?- Are constraints specific (not "be concise" but "under 100 words")?- Does output format match intended use?- Would examples clarify expectations?## Quick Reference: Techniques| Technique | When to Use ||-----------|-------------|| Few-shot | Specific format/style needed || Chain-of-thought | Complex reasoning, math, analysis || Role prompting | Domain expertise, specific tone || Task decomposition | Multi-step workflows || Constraints | Precise requirements |See [references/techniques.md](references/techniques.md) for detailed patterns and examples.## Quick Reference: Output Formats| Format | When to Use ||--------|-------------|| XML tags | Complex prompts, clear section boundaries || JSON | Programmatic parsing, structured data || Markdown | Human-readable reports, documentation |See [references/structured.md](references/structured.md) for format patterns.## System PromptsFor designing AI assistant behavior, see [references/system-prompts.md](references/system-prompts.md).Key sections:- Identity and role definition- Behavioral guidelines- Constraints and boundaries- Output format defaults

Frequently asked questions