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Always-on guidance for solving tasks resourcefully. Teaches agents to escalate through skills, CLI tools, and custom scripts instead of refusing. Applies to any request where the agent lacks a dedicated tool.
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# Resourceful Problem Solving When asked to do something and no dedicated tool exists, follow this escalation pattern: ## 1. Check Skills Use `use_skill` to search for a matching skill. Many common tasks (PDF editing, image generation, GitHub ops, summarization) already have skills available. ## 2. Search for a CLI Tool If no skill matches, check whether a CLI tool exists: ```bash which <tool> # already installed? brew search <tool> # macOS pip search <tool> # Python ecosystem npm search <tool> # Node ecosystem ``` If a suitable tool exists, install it and use it. ## 3. Write a Script If no CLI tool fits, write a short script (Python, Node, or bash) to accomplish the task. Common patterns: - **PDF creation**: Use Python `reportlab` or `fpdf2` - **Image manipulation**: Use Python `Pillow` - **Spreadsheets**: Use Python `openpyxl` or `csv` - **Data conversion**: Use `jq`, `csvkit`, or a short Python script - **Web scraping**: Use `curl` + parsing or Python `requests` + `beautifulsoup4` Install dependencies as needed: `pip install <package>` or `npm install <package>`. ## 4. Save for Reuse If the script solves a task that's likely to come up again, offer to save it as a reusable extension via the `extension_creator` tool. ## Rules - Never refuse a task when shell tools are available. Attempt a code-based solution first. - Only report inability after genuinely trying and failing. - Prefer lightweight, well-known packages over complex bespoke solutions. - Always verify the output before reporting success.
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Always-on guidance for solving tasks resourcefully. Teaches agents to escalate through skills, CLI tools, and custom scripts instead of refusing. Applies to any request where the agent lacks a dedicated tool.
# Resourceful Problem Solving When asked to do something and no dedicated tool exists, follow this escalation pattern: ## 1. Check Skills Use `use_skill` to search for a matching skill. Many common tasks (PDF editing, image generation, GitHub ops, summarization) already have skills available. ## 2. Search for a CLI Tool If no skill matches, check whether a CLI tool exists: ```bash which <tool> # already installed? brew search <tool> # macOS pip search <tool> # Python ecosystem npm search <tool> # Node ecosystem ``` If a suitable tool exists, install it and use it. ## 3. Write a Script If no CLI tool fits, write a short script (Python, Node, or bash) to accomplish the task. Common patterns: - **PDF creation**: Use Python `reportlab` or `fpdf2` - **Image manipulation**: Use Python `Pillow` - **Spreadsheets**: Use Python `openpyxl` or `csv` - **Data conversion**: Use `jq`, `csvkit`, or a short Python script - **Web scraping**: Use `curl` + parsing or Python `requests` + `beautifulsoup4` Install dependencies as needed: `pip install <package>` or `npm install <package>`. ## 4. Save for Reuse If the script solves a task that's likely to come up again, offer to save it as a reusable extension via the `extension_creator` tool. ## Rules - Never refuse a task when shell tools are available. Attempt a code-based solution first. - Only report inability after genuinely trying and failing. - Prefer lightweight, well-known packages over complex bespoke solutions. - Always verify the output before reporting success.