prompting
Prompt engineering standards and context engineering principles for AI agents based on Anthropic best practices. Covers clarity, structure, progressive discovery, and optimization for signal-to-noise ratio.
npx skills add majiayu000/claude-skill-registry --skill multicam-qara-claude-skills-prompting-skill --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Prompting Skill ## When to Activate This Skill - Prompt engineering questions - Context engineering guidance - AI agent design - Prompt structure help - Best practices for LLM prompts - Agent configuration ## Core Philosophy **Context engineering** = Curating optimal set of tokens during LLM inference **Primary Goal:** Find smallest possible set of high-signal tokens that maximize desired outcomes ## Key Principles ### 1. Context is Finite Resource - LLMs have limited "attention budget" - Performance degrades as context grows - Every token depletes capacity - Treat context as precious ### 2. Optimize Signal-to-Noise - Clear, direct language over verbose explanations - Remove redundant information - Focus on high-value tokens ### 3. Progressive Discovery - Use lightweight identifiers vs full data dumps - Load detailed info dynamically when needed - Just-in-time information loading ## Markdown Structure Standards Use clear semantic sections: - **Background Information**: Minimal essential context - **Instructions**: Imperative voice, specific, actionable - **Examples**: Show don't tell, concise, representative - **Constraints**: Boundaries, limitations, success criteria ## Writing
- When to Activate This Skill
- Core Philosophy
- Key Principles
- 1. Context is Finite Resource
- 2. Optimize Signal-to-Noise
- 3. Progressive Discovery
- Markdown Structure Standards
- Writing Style
- Clarity Over Completeness
- Be Direct
- Use Structured Lists
- Context Management
- Just-in-Time Loading
- Structured Note-Taking
What does the prompting skill do?
Prompt engineering standards and context engineering principles for AI agents based on Anthropic best practices. Covers clarity, structure, progressive discovery, and optimization for signal-to-noise ratio.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill multicam-qara-claude-skills-prompting-skill --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.