Borrowing it
Nothing to install: this file belongs to diodeme/Gold-Band. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/diodeme/Gold-Band/main/.agents/skills/enhance-prompt/SKILL.mdgit clone --depth 1 https://github.com/diodeme/Gold-BandWrote 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/diodeme/gold-band/enhance-prompt)<a href="https://agentmods.dev/skills/diodeme/gold-band/enhance-prompt"><img src="https://agentmods.dev/badge/skills/diodeme/gold-band/enhance-prompt/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/diodeme/gold-band/enhance-prompt"><img src="https://agentmods.dev/badge/skills/diodeme/gold-band/enhance-prompt.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 | $0.00041 | $0.01592 |
| Opus 5 | $0.00020 | $0.00796 |
| Sonnet 5 | $0.00008 | $0.00318 |
| Haiku 4.5 | $0.00004 | $0.00159 |
Grade A, and why
enhance-prompt 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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 205 lines · 41 tokens per session scan A ccb200c79807
enhance-prompt is a skill published in the GitHub repository diodeme/Gold-Band (82 stars, last pushed yesterday), licensed AGPL-3.0. It adds 41 tokens to every session and 1,592 once invoked, about $0.0002 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.
Other skills, from other repositories
enhance-prompt
Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.
cordis-plugin-sofagent-inject
A sofagent plugin that loads company constraints through several prompt-building layers when the agent starts.
stitch-ued-guide
Visual vocabulary, design terminology, and prompt engineering strategy for Stitch. Reference this when you need layout pattern names, aesthetic style terms, color structure formulas, or device guidelines.
dataflow-pattern-math-reasoning-sft
Reuse a reviewed pipeline pattern for constructing benchmark-aligned math reasoning SFT records from question-and-answer datasets with verifiable final answers.
ai-interaction-patterns
AI UX patterns — prompt UX, wayfinding, HITL, trust, disclosure, memory, generative UI.
seo-llm
Use when optimizing content for LLM-powered search engines (ChatGPT, Perplexity, Gemini, Claude, Bing AI, Qwen), implementing RAG optimization, prompt engineering for search visibility, semantic SEO, and ensuring content ranks highly in AI-driven search results. Includes techniques for ChatGPT SEO, Perplexity…