# Agricidaniel Claude Prompts Claude Prompts

> Prompt Enhancer

- Skill: `tomevault-io/agricidaniel-claude-prompts-claude-prompts` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tomevault-io/agricidaniel-claude-prompts-claude-prompts`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/agricidaniel-claude-prompts-claude-prompts/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: tomevault-io (https://skillmd.com/u/tomevault-io)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tomevault-io/agricidaniel-claude-prompts-claude-prompts

---


# Prompt Enhancer

Take any existing prompt and supercharge it using techniques from 2,500+ curated prompts.

## Enhancement Workflow

### Step 1: Analyze the Input Prompt

Evaluate the user's prompt on these dimensions:
- **Specificity** (1-5): How detailed is the subject description?
- **Technical quality** (1-5): Camera, lighting, composition details?
- **Style clarity** (1-5): Is the aesthetic clearly defined?
- **Model optimization** (1-5): Uses model-specific syntax correctly?
- **Length appropriateness** (1-5): Right length for the target model?

Present a brief score card before enhancing.

### Step 2: Find Similar Top Prompts

Search for high-quality reference prompts:
```bash
python3 {PROMPT_ENGINE_DIR}/scripts/search_prompts.py "KEY_TERMS" --limit 5
```

### Step 3: Apply Enhancement Techniques

Choose from these enhancement strategies based on what's missing:

**Detail Injection** (for low specificity):
- Add material textures ("brushed aluminum", "weathered leather")
- Add environmental details ("dust particles in light", "morning dew")
- Add character details ("freckled skin", "calloused hands")

**Technical Elevation** (for missing camera/lighting):
- Add camera specs ("shot on Canon R5, 85mm f/1.2")
- Add lighting ("golden hour backlighting", "Rembrandt lighting")
- Add film stocks ("Kodak Portra 400 colors", "Fuji Velvia saturation")

**Style Anchoring** (for unclear aesthetic):
- Add photographer/artist references ("in the style of Annie Leibovitz")
- Add film/era references ("Y2K aesthetic", "1970s Kodachrome")
- Add mood keywords ("moody", "ethereal", "gritty")

**Negative Refinement** (for models that support it):
- Add negative prompts to exclude unwanted elements
- Specify what NOT to include ("no text", "no watermark")

**Structure Optimization** (for poor organization):
- Reorder elements: subject first, then environment, then style
- Group related modifiers together
- Remove redundant or conflicting terms

### Step 4: Present Enhanced Version

Output format:
1. **Original prompt** (for comparison)
2. **Enhanced prompt** (the improved version)
3. **What changed** (bullet list of specific improvements)
4. **Score improvement** (before -> after on 5-point scale)
5. **Variations** (2-3 alternative enhanced versions)

## Enhancement Rules

- Never remove the user's core intent/subject
- Preserve the user's preferred style if stated
- Keep enhancements relevant to the target model
- Don't over-engineer: some prompts are intentionally minimal
- Always explain WHY each change was made

---
> Source: [AgriciDaniel/claude-prompts](https://github.com/AgriciDaniel/claude-prompts) — distributed by [TomeVault](https://tomevault.io).
<!-- tomevault:4.0:skill_md:2026-06-21 -->