EconSkills: Studying Skill Transfer and Retrieval for Web Agents on Live Economic Data
Yinzhu Quan and Zefang Liu distill verified EconWebArena trajectories into parameterized standard operating procedures for retrieving live economic data and separate skill transfer from skill retrieval.
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Each skill records five fields. Scope, navigation procedure, site-specific guidance, verification checks and recovery steps, with source-instance values replaced by placeholders.
Abstraction beats replay. In controlled transfer, matched skills raise success over no-skill prompting and need fewer steps on paired successes, and parameterized procedures work substantially better than replaying raw trajectories.
At library scale the gain disappears. Retrieval is only competitive with the no-skill baseline overall; it wins on directly covered tasks while approximate matches on uncovered tasks offset those gains.
That result names the open problem. Coverage-aware selection and context delivery, not skill extraction, is what determines whether a skill library pays at scale.
Abstract
Web agents often revisit the same sites, yet most evaluations discard the procedures learned in earlier successful interactions. We introduce EconSkills, a skill library and evaluation framework that distills verified EconWebArena trajectories into parameterized standard operating procedures for retrieving live economic data. Each skill records its scope, navigation procedure, site-specific guidance, verification checks, and recovery steps while replacing source-instance values with placeholders. EconSkills separates two questions: whether a known relevant procedure transfers to a held-out task, and whether an agent can retain that benefit when selecting from a library. In controlled transfer, matched skills improve success over no-skill prompting and require fewer steps on paired successes, while abstraction is substantially more effective than replaying raw trajectories. At library scale, retrieval is competitive with the no-skill baseline overall and performs best on directly covered tasks; coverage-stratified outcomes show that approximate matches on uncovered tasks offset these gains. Browser trajectories further identify when procedural guidance shortens portal-specific navigation and when semantic verification remains necessary. These results establish that reusable economic web procedures can transfer across task instances and provide a concrete design target for coverage-aware selection and context delivery.