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Fix all long sentences in context engineering documentation
Split 5 sentences over 25 words in context-enginerring.md:
- Line 19: Context sending (27 → 13, 14, 10 words)
- Line 41: Context drift (32 → 18, 18 words)
- Line 56: Information overload (32 → 24, 9 words)
- Line 66: Request effectiveness (26 → 12, 12 words) + fixed typo "mainatin"
- Line 73: Tool management (27 → 21, 8 words)
Additional improvements:
- Changed "completely" to "fully" for better readability
- Changed "simple" to "basic" for more accurate description
- Minor updates to best-practice/README.md and available-tools.md
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Copy file name to clipboardExpand all lines: 16/umbraco-cms/reference/developer-mcp/best-practice/README.md
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@@ -101,10 +101,10 @@ Tips for Better Prompting
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Instead of:
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Fix this content model.
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Use:
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Update the document type to include a new "SEO Description" property and apply it to all "Blog Post" nodes.
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Update the Document Type to include a new "SEO Description" property and apply it to all "Blog Post" nodes.
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-**Mention tools or entities by name**
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If you've enabled tools like document-type, media, or data-type, refer to them directly in your prompt to help the model understand what it can access.
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If you've enabled tools like ```document-type, media, or data-type```, refer to them directly in your prompt to help the model understand what it can access.
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-**Use system instructions or context files for background**
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Offload rules, terminology, or structural constraints into a dedicated instruction file. This keeps prompts cleaner and context more focused.
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Don’t try to do everything in one prompt. Sequence multi-step operations (e.g., create types → add content → apply relations) across multiple turns for better results.
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{% hint style="info" %}
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If a prompt fails or produces a weak result, try these approaches. Simplify it, restate it with clearer intent, or reduce the number of active tools.
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If a prompt fails or produces a weak result, try these approaches: simplify it, restate it with clearer intent, or reduce the number of active tools.
Copy file name to clipboardExpand all lines: 16/umbraco-cms/reference/developer-mcp/concepts/context-enginerring.md
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@@ -4,7 +4,7 @@ description: Effective and optimal communication with LLMs
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# Context engineering
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Context Engineering is the foundation of any interaction with with any large language models (LLMs) and consequently the best way to control how the Umbraco Developer MCP Server delivers precise, reliable, and efficient responses. It’s all about shaping what the LLM sees and how it understands your request so that it can make the best responses.
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Context Engineering is the foundation of any interaction with large language models (LLMs). This practice controls how the Umbraco Developer MCP Server delivers precise, reliable, and efficient results. It shapes what the LLM sees and understands about your request to produce the best possible responses.
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## What is Context
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LLMs are stateless — they don’t support retaining information between individual requests. Each time you send a message, the entire context (conversation history + any injected system data) is sent to the model to generate a new response.
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LLMs are stateless — they don't support retaining information between individual requests. Each time you send a message, the entire context is sent to the model. This includes conversation history and any injected system data.
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**You can never completely control what an LLM with return.
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**You can never fully control what an LLM with return.
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You can influence the outcome — and context is the only way that you do that.**
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{% hint style="info" %}
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## Why Context Engineering Is So Important
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In the early days of large language models (LLMs), the context of a conversation was simple — just your messages and the model’s responses.
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Conversations were short and easy to follow, but even then, you could see context drift — as earlier parts of the discussion faded, the model’s memory weakened and response quality declined.
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In the early days of large language models (LLMs), the context of a conversation was straightforward — only your messages and the model's responses.
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Conversations were short and easy to follow, but even then, you could see context drift. As earlier parts of the discussion faded, the model's memory weakened and response quality declined.
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Today, however, the landscape has changed dramatically.
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If too much irrelevant or poorly structured or contradictory information is included, useful parts of the context may get pushed out or forgotten, leading to confusion, incomplete answers, or hallucinations.
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If too much irrelevant, poorly structured, or contradictory information is included, useful parts of the context may get pushed out or forgotten. This leads to confusion, incomplete answers, or hallucinations.
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That’s why **context engineering is more important now than ever** — it’s about managing this limited space carefully and intentionally.
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{% hint style="info" %}
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## How this affects the Umbraco CMS developer MCP
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In the Umbraco CMS Developer MCP (Model Context Protocol), context engineering is applied through structured tool contexts and well-defined prompts.
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Doing this makes requests more effective, **efficient, and more likely to succeed** — and also makes **prompts easier to write, reuse and mainatin**.
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This makes requests more effective, efficient, and more likely to succeed. It also makes prompts easier to write, reuse, and maintain.
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{% hint style="info" %}
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Think of context engineering as the art of precision storytelling: every piece of information you include should help the model stay on track and deliver value.
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{% endhint %}
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Your choice of enabled tools directly shapes the quality of your context.
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By managing which tools and tool collections are active, you control how much information is sent to the model — improving both performance and response reliability.
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By managing which tools and tool collections are active, you control how much information is sent to the model. This improves both performance and response reliability.
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For more information, see [Tool Collections](../available-tools.md)
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