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 5.5 | $0.00014 | $0.00116 |
| Sonnet 5.5 | $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 1mo 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.
- 1mo 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 (90 stars, last pushed 7d ago), licensed MIT. It adds 34 tokens to every session and 289 once invoked, about $0.0001 per session on Opus 5.5. 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
claude
Expert Anthropic Claude API assistance covering Claude 3.5 Sonnet / Haiku / Opus, tool use, prompt caching, and long-context processing. Use when integrating Anthropic models into LLM applications.
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.
llm-prompt-optimizer
Use when improving prompts for any LLM. Applies proven prompt engineering techniques to boost output quality, reduce hallucinations, and cut token usage.
claude-api
Build apps with the Claude API or Anthropic SDK. TRIGGER when: code imports anthropic/@anthropic-ai/sdk/claudeagentsdk, or user asks to use Claude API, Anthropic SDKs, or Agent SDK. DO NOT TRIGGER when: code imports openai/other AI SDK, general programming, or ML/data-science tasks.
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.
llm-application-dev-prompt-optimize
You are an expert prompt engineer specializing in crafting effective prompts for LLMs through advanced techniques including constitutional AI, chain-of-thought reasoning, and model-specific optimizati.