boost-prompt

Interactive prompt refinement workflow: interrogates scope, deliverables, constraints; copies final markdown to clipboard; never writes code. Requires the Joyride extension.

23 stars

Best use case

boost-prompt is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Interactive prompt refinement workflow: interrogates scope, deliverables, constraints; copies final markdown to clipboard; never writes code. Requires the Joyride extension.

Teams using boost-prompt should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/boost-prompt/SKILL.md --create-dirs "https://raw.githubusercontent.com/christophacham/agent-skills-library/main/skills/ai-ml/boost-prompt/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/boost-prompt/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How boost-prompt Compares

Feature / Agentboost-promptStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Interactive prompt refinement workflow: interrogates scope, deliverables, constraints; copies final markdown to clipboard; never writes code. Requires the Joyride extension.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

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_input` tool.
- 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:

```clojure
(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.

Related Skills

tldr-prompt

23
from christophacham/agent-skills-library

Create tldr summaries for GitHub Copilot files (prompts, agents, instructions, collections), MCP servers, or documentation from URLs and queries.

customaize-agent:test-prompt

23
from christophacham/agent-skills-library

Use when creating or editing any prompt (commands, hooks, skills, subagent instructions) to verify it produces desired behavior - applies RED-GREEN-REFACTOR cycle to prompt engineering using subagents for isolated testing

prompt-library

23
from christophacham/agent-skills-library

Curated collection of high-quality prompts for various use cases. Includes role-based prompts, task-specific templates, and prompt refinement techniques. Use when user needs prompt templates, role-...

customaize-agent:prompt-engineering

23
from christophacham/agent-skills-library

Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.

prompt-engineering-patterns

23
from christophacham/agent-skills-library

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing productio...

prompt-engineer

23
from christophacham/agent-skills-library

Transforms user prompts into optimized prompts using frameworks (RTF, RISEN, Chain of Thought, RODES, Chain of Density, RACE, RISE, STAR, SOAP, CLEAR, GROW)

prompt-caching

23
from christophacham/agent-skills-library

Caching strategies for LLM prompts including Anthropic prompt caching, response caching, and CAG (Cache Augmented Generation) Use when: prompt caching, cache prompt, response cache, cag, cache augm...

prompt-builder

23
from christophacham/agent-skills-library

Guide users through creating high-quality GitHub Copilot prompts with proper structure, tools, and best practices.

llm-application-dev-prompt-optimize

23
from christophacham/agent-skills-library

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

finalize-agent-prompt

23
from christophacham/agent-skills-library

Finalize prompt file using the role of an AI agent to polish the prompt for the end user.

enhance-prompts

23
from christophacham/agent-skills-library

Use when improving general prompts for structure, examples, and constraints.

enhance-agent-prompts

23
from christophacham/agent-skills-library

Use when improving agent prompts, frontmatter, and tool restrictions.