Instead of overloading the context window, encapsulate deep domain knowledge into "skill" files. Claude Code can then intelligently pull in this information "just-in-time" when it needs to perform a specific task, like following a complex architectural pattern.

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For niche tasks, leverage an AI model with deep domain knowledge (like Claude for its own 'Skills' feature) to create highly specific prompts. Then, feed these optimized prompts into a powerful, generalist coding assistant (like Google's) to achieve a more accurate and robust final product.

The concept isn't about fitting a massive codebase into one context window. Instead, it's a sophisticated architecture using a deep relational knowledge graph to inject only the most relevant, line-level context for a specific task at the exact moment it's needed.

Structure AI context into three layers: a short global file for universal preferences, project-specific files for domain rules, and an indexed library of modular context files (e.g., business details) that the AI only loads when relevant, preventing context window bloat.

The concept of "Skills" was born when the team found that telling Claude *how* to query a data source and follow design guidelines produced better, more flexible dashboards than building rigid, parameterized tools. This discovery highlighted the power of instruction over hard-coding.

Overloading LLMs with excessive context degrades performance, a phenomenon known as 'context rot'. Claude Skills address this by loading context only when relevant to a specific task. This laser-focused approach improves accuracy and avoids the performance degradation seen in broader project-level contexts.

The tangible asset for a Claude Skill is surprisingly low-tech: a folder containing a 'skills.md' file and other optional resources. This folder is either referenced by Claude in a local directory or zipped and uploaded to the web UI, demystifying the creation process for non-engineers.

Instead of uploading brand guides for every new AI task, use Claude's "Skills" feature to create a persistent knowledge base. This allows the AI to access core business information like brand voice or design kits across all projects, saving time and ensuring consistency.

AI has no memory between tasks. Effective users create a comprehensive "context library" about their business. Before each task, they "onboard" the AI by feeding it this library, giving it years of business knowledge in seconds to produce superior, context-aware results instead of generic outputs.

You don't need a special command like 'invoke skill' to activate a Claude Skill. The AI agent automatically detects when a skill is relevant based on the context of the conversation. For example, simply pasting a changelog can trigger a 'changelog-to-newsletter' skill without any other instruction.

Unlike Claude Projects or OpenAI's Custom GPTs which apply a general context to all chats, Claude Skills are task-specific instruction sets that can be dynamically called upon within any conversation. This allows for reusable, on-demand workflows without being locked into a specific project's context.

Use "Skills" to Give Claude Code Just-in-Time Access to Domain Knowledge | RiffOn