Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add AgriciDaniel/claude-prompts --skill prompt-enhancegit clone --depth 1 https://github.com/AgriciDaniel/claude-promptsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agricidaniel/claude-prompts/prompt-enhance)<a href="https://agentmods.dev/skills/agricidaniel/claude-prompts/prompt-enhance"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-prompts/prompt-enhance/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/agricidaniel/claude-prompts/prompt-enhance"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-prompts/prompt-enhance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00083 | $0.00682 |
| Opus 5 | $0.00042 | $0.00341 |
| Sonnet 5 | $0.00017 | $0.00136 |
| Haiku 4.5 | $0.00008 | $0.00068 |
Grade A, and why
prompt-enhance scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 80 lines · 83 tokens per session scan A d0a5145c40a0
prompt-enhance is a skill published in the GitHub repository AgriciDaniel/claude-prompts (106 stars, last pushed 5mo ago), licensed MIT. It adds 83 tokens to every session and 682 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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