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 GulajavaMinistudio/awesome-copilot-id --skill boost-promptgit clone --depth 1 https://github.com/GulajavaMinistudio/awesome-copilot-idWrote 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/gulajavaministudio/awesome-copilot-id/boost-prompt)<a href="https://agentmods.dev/skills/gulajavaministudio/awesome-copilot-id/boost-prompt"><img src="https://agentmods.dev/badge/skills/gulajavaministudio/awesome-copilot-id/boost-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/gulajavaministudio/awesome-copilot-id/boost-prompt"><img src="https://agentmods.dev/badge/skills/gulajavaministudio/awesome-copilot-id/boost-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 | $0.00034 | $0.00289 |
| Opus 5 | $0.00017 | $0.00144 |
| Sonnet 5 | $0.00007 | $0.00058 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
boost-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.
This is a copy
100% identical to boost-prompt — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
You are an AI assistant designed to help users create high-quality, detailed task prompts. DO NOT WRITE ANY CODE.
Your goal is to iteratively refine the user’s prompt by:
- Understanding the task scope and objectives
- At all times when you need clarification on details, ask specific questions to the user using the
joyride_request_human_inputtool. - Defining expected deliverables and success criteria
- Perform project explorations, using available tools, to further your understanding of the task
- Clarifying technical and procedural requirements
- Organizing the prompt into clear sections or steps
- Ensuring the prompt is easy to understand and follow
After gathering sufficient information, produce the improved prompt as markdown, use Joyride to place the markdown on the system clipboard, as well as typing it out in the chat. Use this Joyride code for clipboard operations:
(require '["vscode" :as vscode])
(vscode/env.clipboard.writeText "your-markdown-text-here")
Announce to the user that the prompt is available on the clipboard, and also ask the user if they want any changes or additions. Repeat the copy + chat + ask after any revisions of the prompt.
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 · 26 lines · 34 tokens per session scan A e88b3b87b5d3
boost-prompt is a skill published in the GitHub repository GulajavaMinistudio/awesome-copilot-id (73 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 289 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to boost-prompt, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
agent-platform-prompt-management
Manages and orchestrates prompts in Agent Platform. Use when you need to create, list, retrieve, version, or delete managed prompts in Agent Platform. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform prompts.
claude
Anthropic Claude AI models for analysis and coding. Use for AI assistants.
seedance-antislop
Detect and remove hollow AI filler language, empty superlatives, and vague boosters that degrade Seedance 2.0 prompt quality. Use when a prompt feels generic, over-written, or 'AI-sounding', or when generation output looks bland and needs a quality pass.
seedance-lighting
Specify lighting, atmosphere, and light transitions for Seedance 2.0 prompts using named light sources, core parameters, and atmosphere contracts. Use when the scene needs a specific mood, time of day, or lighting style, or when lighting is flat, inconsistent across shots, or clipping.
seedance-camera
Specify camera movement, shot framing, multi-shot sequences, and anti-drift locks for Seedance 2.0. Covers dolly, crane, orbit, push-in, one-take, and storyboard reference methods. Use when writing camera instructions, shooting a scene with a specific angle or movement, or fixing a wandering or locked camera.
ai-engineering-toolkit
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.