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desilokesh1desilokesh1/antigravity-fullstack-hq/skills/prompt-engineering/SKILL.md

prompt-engineering

Skill2 starsChanged 10 months agoMITView on GitHub

Comprehensive prompt engineering framework for designing, optimizing, and iterating LLM prompts. Use when creating prompts, optimizing existing prompts, or improving AI instructions.

85 other projects use a version of this.

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Projects with it also use security-checklist, multi-agent-orchestration and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 74 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Before creating any prompt, understand:

    line 20

“Common” is measured: kept by at least 6 in 10 of the 74 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Prompt Engineering

Workflow

User Request
|
+-- "Create a prompt" --> EXPLORATION PHASE
+-- "Optimize this prompt" --> OPTIMIZATION PHASE
+-- "Fix this issue" --> ANALYSIS PHASE

Phase 1: Exploration

Before creating any prompt, understand:

  • What task will this prompt accomplish?
  • Who will use it?
  • What does success look like?
  • What are the constraints?

Phase 2: Analysis

Task Classification

DimensionOptions
ComplexitySimple vs multi-step
OutputCreative vs analytical vs structured
StakesHigh vs experimental

Strategy Selection

Task TypeApproach
SimpleDirect instructions
ComplexChain-of-thought
CreativeRole setting
StructuredFormat specs + examples

Phase 3: Implementation

Version 1 - Minimal

  • Core instructions only
  • Test basic functionality

Version 2 - Enhanced

  • Add examples
  • Clarify ambiguities
  • Add constraints

Version 3+ - Optimized

  • Refine wording
  • Remove redundancy

Key Techniques

Role Setting

As an experienced code reviewer, analyze...

Chain-of-Thought

Think step-by-step:
1. First, identify...
2. Then, analyze...
3. Finally, conclude...

Few-Shot Learning

Example 1:
Input: "Great product"
Output: { "sentiment": "positive" }

Now analyze: "It was okay"

Explicit Constraints

- Limit to 3 paragraphs
- Focus on technical aspects only
- Do not include pricing

Prompt Template

## Context
[Background information]

## Role (Optional)
You are a [ROLE] with expertise in [DOMAIN].

## Task
[Clear instruction]

## Constraints
- Constraint 1
- Constraint 2

## Output Format
[Format specification]

## Examples (Optional)
[Input/Output examples]

Common Mistakes

MistakeFix
Vague instructionsBe specific
No examplesAdd 1-2 examples
Too many rulesSimplify
No format specDefine output structure

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