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 mehdiozdemir/awesome-agent-skills --skill prompt-enhancergit clone --depth 1 https://github.com/mehdiozdemir/awesome-agent-skillsWrote 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/mehdiozdemir/awesome-agent-skills/prompt-enhancer)<a href="https://agentmods.dev/skills/mehdiozdemir/awesome-agent-skills/prompt-enhancer"><img src="https://agentmods.dev/badge/skills/mehdiozdemir/awesome-agent-skills/prompt-enhancer/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/mehdiozdemir/awesome-agent-skills/prompt-enhancer"><img src="https://agentmods.dev/badge/skills/mehdiozdemir/awesome-agent-skills/prompt-enhancer.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 | $0.00056 | $0.04206 |
| Opus 5 | $0.00028 | $0.02103 |
| Sonnet 5 | $0.00011 | $0.00841 |
| Haiku 4.5 | $0.00006 | $0.00421 |
Grade A, and why
prompt-enhancer 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 — 636 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prompt Enhancer Skill
This skill transforms basic, vague, or poorly structured prompts into clear, specific, and highly effective instructions that produce superior AI outputs. Use this whenever someone needs to improve their prompt quality or wants to get better results from AI models.
Core Principles of Effective Prompts
1. Clarity & Specificity
- Remove ambiguity and vague language
- Define exact requirements and constraints
- Specify format, length, and structure expectations
- Clarify the intended audience and purpose
2. Context Provision
- Include relevant background information
- Define the domain and subject matter
- Specify the user's skill level and knowledge
- Provide examples when helpful
3. Structure & Organization
- Break complex requests into clear steps
- Use numbered lists for sequential tasks
- Use bullet points for parallel requirements
- Organize information hierarchically
4. Role & Persona Definition
- Specify the AI's role or expertise level
- Define the tone and style (formal, casual, technical, etc.)
- Set constraints on the response format
- Clarify the relationship to the user
5. Output Specification
- Define expected format (markdown, JSON, code, etc.)
- Specify length requirements
- Request specific sections or components
- Define success criteria
Enhancement Process
Step 1: Analyze the Original Prompt
Identify issues:
- Vague or unclear requirements
- Missing context or constraints
- Ambiguous language
- Lack of structure
- Missing output specifications
- Insufficient examples
Step 2: Extract Intent
Determine:
- What is the user really trying to achieve?
- What is the expected output?
- Who is the intended audience?
- What level of detail is needed?
- What constraints exist?
Step 3: Enhance Systematically
Apply these improvements:
Add Missing Elements:
- Context and background
- Specific requirements
- Output format specifications
- Examples (when helpful)
- Constraints and limitations
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 · 636 lines · 56 tokens per session scan A 1561524e85cf
prompt-enhancer is a skill published in the GitHub repository mehdiozdemir/awesome-agent-skills (2 stars, last pushed 7mo ago), licensed MIT. It adds 56 tokens to every session and 4,206 once invoked, about $0.0003 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 2026-08-31.
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