render-claude-context

The render-claude-context skill is designed to automate the collection of CLAUDE.md files from a project's directory hierarchy, extending up to the ~/.claude/ directory. By embedding the relevant @-imports and commands from these files, it generates processed context files that can be utilized with other AI agents. This automation simplifies the process of context preparation, allowing users to focus on more critical tasks without the manual overhead of file management. One of the key benefits of using the render-claude-context skill is the significant reduction in time spent on context file generation. Although specific time savings are currently unknown, the skill's intermediate implementation time of just 30 minutes suggests that users can quickly integrate it into their workflows. By automating the tedious task of gathering and processing context data, developers and AI practitioners can streamline their operations, leading to increased productivity and efficiency. This skill is particularly beneficial for developers, product managers, and AI practitioners who work with AI agents and require a structured context for their operations. It is ideal for teams looking to enhance their workflow automation capabilities, especially in environments where multiple CLAUDE.md files are in use. For instance, a development team could use this skill to ensure that all relevant context is readily available for their AI agents, thereby improving the agents' performance in executing tasks. With an intermediate level of complexity, the render-claude-context skill requires some familiarity with directory structures and file management. However, its ease of implementation makes it accessible to a wide range of users. By incorporating this skill into an AI-first workflow, teams can ensure that their AI agents have the necessary context to operate effectively, ultimately leading to better outcomes and more efficient project execution.

1. **Install the skill**: Ensure your AI assistant supports file system operations (e.g., Claude Code or a local LLM with file access). 2. **Run the scan**: Execute the prompt template in your terminal or AI assistant, replacing `[PROJECT_FOLDER]` with your project directory (e.g., `/Users/yourname/projects/acme-corp`) and `[OUTPUT_PATH]` with your desired output file (e.g., `./acme-corp.context.md`). 3. **Verify imports**: Check the generated file for `@import` and `@command` entries. Ensure all referenced files exist and contain valid commands. 4. **Use with Sortd**: Load the generated context file into Sortd’s kanban boards to automate workflows. For example, use `@command /update-deal-stage` to move deals between Sortd’s "In Progress" and "Closed Won" columns. 5. **Iterate**: Update CLAUDE.md files in your project or global `.claude/` directory to include new commands or imports. Re-run the skill to regenerate the context file. **Tips**: - Use absolute paths for `@import` and `@command` entries to avoid ambiguity. - For Sortd integration, name your Sortd boards to match imported workflow files (e.g., `sales-pipeline.md` → Sortd board "Sales Pipeline"). - Store global commands in `~/.claude/globals/` to reuse them across projects.