A method, device, and storage medium for skill recursive nesting.

By building a skill library and providing a unified calling interface and metadata structure, and adopting a recursive nested calling method, the problem of rigid function combination in existing technologies is solved, which improves flexibility and reusability and reduces maintenance costs.

CN122309081APending Publication Date: 2026-06-30BEIJING CHENGSHI WANGLIN INFORMATION TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING CHENGSHI WANGLIN INFORMATION TECH CO LTD
Filing Date
2026-04-03
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

In existing technologies, the binary architecture used for function combination and call management leads to rigid combination relationships, poor flexibility, low reusability, high maintenance costs, and an inability to achieve nested structures between package templates.

Method used

A skill library is built to uniformly store atomic skills and combined skills, and a unified callable interface and metadata structure are provided for both types of skills. By recursively nesting methods, combined skills can be called like atomic skills, enabling nesting and reuse at any depth.

Benefits of technology

It improves the flexibility and reusability of function combinations, reduces maintenance costs, avoids redundant configuration issues, and enables the construction of function combination relationships on demand.

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Abstract

This application provides a method, device, and storage medium for skill recursive nesting. In this embodiment, a skill library storing atomic skills and combined skills is pre-built, and a unified callable interface and metadata structure are provided for both types of skills. Based on this approach, when creating a target combined skill, atomic skills and / or combined skills can be selected from the skill library for combination, allowing the combined skill to be called by other combined skills like an atomic skill, thereby achieving recursive nesting and reuse at any depth. When calling the target combined skill, each sub-skill can be parsed and recursively executed according to a pre-defined nested call sequence until the underlying functions are deployed level by level, thus avoiding redundant configuration and improving the reusability of atomic and combined skills. This allows functional combination relationships to be built on demand, thereby improving the flexibility and reusability of functional combinations and reducing maintenance costs.
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