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Template for creating new Agent Skills for context engineering. Use this template when adding new skills to the collection.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
A comprehensive collection of Agent Skills for context engineering, multi-agent architectures, and production agent systems. Use when building, optimizing, or debugging agent systems that require effective context management.
This skill should be used when the user asks to "fine-tune on books", "create SFT dataset", "train style model", "extract ePub text", or mentions style transfer, LoRA training, book segmentation, or author voice replication.
This skill should be used when the user asks to "write a post", "check my voice", "look up contact", "prepare for meeting", "weekly review", "track goals", or mentions personal brand, content creation, network management, or voice consistency.
Production-grade techniques for evaluating LLM outputs using LLMs as judges. Use when implementing LLM-as-judge, comparing model outputs, creating evaluation rubrics, mitigating evaluation bias, or building automated quality assessment pipelines.
Transforms external RDF context into agent mental states (beliefs, desires, intentions) using formal BDI ontology patterns. Use when modeling agent mental states, implementing BDI architecture, transforming RDF to beliefs, or building cognitive agents with neuro-symbolic AI integration.
Strategies for compressing context when agent sessions exceed limits. Use when compressing context, summarizing conversation history, implementing compaction, reducing token usage, or optimizing tokens-per-task for long-running agent sessions.
| name | template |
| description | Template for creating new Agent Skills for context engineering. Use this template when adding new skills to the collection. |
Provide a clear, concise description of what this skill covers and when to use it. This description appears in skill discovery and should help agents (and humans) determine when this skill is relevant.
Important: Keep the total SKILL.md body under 500 lines for optimal performance. Move detailed reference material to separate files in the references/ directory.
Describe specific situations, tasks, or contexts where this skill should be activated. Include both direct triggers (specific keywords or task types) and indirect signals (broader patterns that indicate skill relevance).
Write in third person. The description is injected into the system prompt, and inconsistent point-of-view can cause discovery problems.
Explain the fundamental concepts covered by this skill. These are the mental models, principles, or frameworks that the skill teaches.
Default assumption: Claude is already very smart. Only add context Claude does not already have. Challenge each piece of information:
Provide detailed explanation of the first major topic. Include specific techniques, patterns, or approaches. Use examples to illustrate concepts.
Provide detailed explanation of the second major topic. Continue with additional topics as needed.
For longer topics, consider moving content to references/ and linking:
Provide actionable guidance for applying the skill. Include common patterns, anti-patterns to avoid, and decision frameworks for choosing between approaches.
Match the level of specificity to the task's fragility:
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Example:
Input: [describe input]
Output: [show expected output]
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Created: [Date] Last Updated: [Date] Author: [Author or Attribution] Version: [Version number]