Architect skills as modular blocks to control token usage and complexity. Triggers: skills, architecture, modular, design-patterns, modularity, skill design, skill architecture, modularization, token optimization, skill structure, refactoring skills, new skill creation, skill complexity. Use when creating skills >150 lines, breaking down monolithic skills, or planning new architecture. Do not use for evaluating existing skills (use skills-eval) or writing human-facing prose (use writing-clearly-and-concisely). Check this skill before starting any new skill development.
6.6
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Well-structured skill addressing a real pain point in AI agent skill development. The description clearly defines scope with specific triggers and usage scenarios. Task knowledge is comprehensive with concrete tools (analyze.py, tokens.py, module-validator) and actionable workflows. Structure is exemplary: concise SKILL.md with clear TOC, progressive disclosure, and references to detailed modules. The hub-and-spoke model is well-executed. Novelty is strong—modular skill architecture with token optimization is sophisticated work that would require significant agent context otherwise. Minor improvements could include more explicit decision trees (e.g., 'if lines > X, do Y') and clearer success criteria for validation steps. The skill practices what it preaches with good modularity and concrete examples throughout.
athola
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