Designing, refining, and maintaining agent skills at Perplexity

Perplexity’s guide to Agent Skills describes them as modular, progressively loaded packages of context, instructions, code, references, and assets that help agents perform specialized tasks more reliably than general model knowledge alone. Unlike conventional software, effective Skills prioritize dense, high-value guidance, carefully curated hierarchy, conditional information loading, and detailed “gotchas” that address known failure modes, while avoiding obvious instructions the model already knows. Each Skill’s concise description is especially important because it determines when the agent loads it, and poorly scoped routing can cause unwanted overlap with other Skills. The guide recommends determining whether a Skill is necessary through real-task testing, writing evaluations before implementation, using positive and negative routing examples, placing heavy or conditional material in auxiliary files, and iterating extensively before release. Ongoing maintenance should focus on evaluated routing changes, accumulating failure-derived guidance, progressive-loading checks, end-to-end task evaluations, and testing across model families. Although Skills can automate recurring workflows and encode domain expertise or organizational preferences, the guide emphasizes that every Skill consumes context and requires careful curation, making brevity, specificity, and necessity central design principles.

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