A method and apparatus for operating skill management

Abstract

This invention discloses a method and apparatus for managing operational skills, relating to the field of computer technology. One specific implementation of the method includes: responding to a skill teaching instruction, activating the operation interface of a business system, starting a background monitoring service, whereby the background monitoring service captures in real-time the user's operational steps on the operation interface and the business system's feedback information on these steps; generating operation logs based on the operational steps and feedback information and storing them in the monitoring log; reading the latest operation logs in real-time from the monitoring logs of the background monitoring service, parsing them to generate operation step description information; responding to the user's interactive correction operation on the operation step description information, obtaining the corrected operation step description information, and sequentially summarizing the operation step description information according to the generation order to generate operational skills. This implementation can efficiently convert user operational experience into standardized, reusable operational skills, thereby improving the accuracy of business process execution and the efficiency of experience transfer.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to an operational skills management method and apparatus. Background Technology

[0002] In the current digital transformation of government affairs, complex business processes that heavily rely on personal experience are difficult to replicate at scale. Existing technologies have significant shortcomings: traditional customized business system solutions require professional developers to design and code the system, and business experts convey experience through written materials or verbal descriptions, which leads to problems such as distorted experience transmission, long development cycles, and high user learning costs; while skill generation solutions based on natural language descriptions suffer from information loss due to reliance on language and text intermediaries, making it difficult to meet the accuracy and reliability requirements of complex operations in government business scenarios. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide an operational skills management method and apparatus, which can at least solve the problems of distorted experience transfer, long development cycle, high user learning cost, and information loss due to reliance on language and text as intermediaries in the prior art.

[0004] To achieve the above objectives, according to one aspect of the present invention, an operational skill management method is provided, comprising: In response to the skills teaching instruction, the operation interface of the business system is activated, and the background monitoring service is started at the same time. The background monitoring service captures the user's operation steps on the operation interface in real time, as well as the feedback information of the business system on the operation steps. Based on the operation steps and the feedback information, an operation log is generated and stored in the monitoring log. The latest operation logs are read in real time from the monitoring logs of the background monitoring service, and the operation steps and feedback information in the latest operation logs are parsed to generate operation step description information. In response to the user's interactive correction of the operation step description information, the corrected operation step description information is obtained, and the operation step description information is summarized in the order of generation to generate operation skills.

[0005] To achieve the above objectives, according to another aspect of the present invention, an operational skill management device is provided, comprising: The capture module is used to respond to skill teaching instructions, wake up the operation interface of the business system, and start the background monitoring service at the same time. This allows the background monitoring service to capture the user's operation steps on the operation interface in real time, as well as the feedback information of the business system to the operation steps. Based on the operation steps and the feedback information, it generates operation logs and stores them in the monitoring log. The parsing module is used to read the latest operation logs in real time from the monitoring logs of the background monitoring service, and parse the operation steps and feedback information in the latest operation logs to generate operation step description information. The correction module is used to respond to the user's interactive correction operation on the operation step description information, obtain the corrected operation step description information, and summarize the operation step description information in the order of generation to generate operation skills.

[0006] To achieve the above objectives, according to another aspect of the present invention, an electronic device for managing operational skills is provided.

[0007] The electronic device of this invention includes: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement any of the above-described operation skill management methods.

[0008] To achieve the above objectives, according to another aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements any of the above-described operation skill management methods.

[0009] To achieve the above objectives, according to another aspect of the present invention, a computing program product is provided. One such computing program product includes a computer program that, when executed by a processor, implements the operation skill management method provided in this embodiment of the invention.

[0010] According to the solution provided by the present invention, one embodiment of the invention has the following advantages or beneficial effects: by capturing and parsing operation steps in real time, the user's operational experience on the operation interface can be converted into standardized and reusable operational skills, thereby avoiding the problem of experience loss caused by personnel turnover and significantly reducing the threshold for skill transfer, enabling newcomers to quickly master complex business operations without long-term practice. This method improves business processing efficiency by ensuring a high degree of match between the generated operational skills and actual business experience through real-time capture and parsing and user feedback correction mechanisms, thereby improving the accuracy of complex business process execution.

[0011] The further effects of the aforementioned unconventional alternative methods will be explained below in conjunction with specific implementation methods. Attached Figure Description

[0012] The accompanying drawings are provided to better understand the invention and are not intended to unduly limit the scope of the invention. Wherein: Figure 1 This is a schematic diagram of the main process of an operational skills management method according to an embodiment of the present invention; Figure 2This is an interactive diagram illustrating the skill generation process; Figure 3(a) is a schematic diagram of the operation entry interface; Figure 3(b) is a schematic diagram of the interface in recording mode; Figure 3(c) is a schematic diagram of the interface in the paused recording state; Figure 4 A flowchart illustrating an optional operational skill management method according to an embodiment of the present invention; Figure 5(a) is an interactive schematic diagram of the process of generating new operation skills through iterative optimization; Figure 5(b) is an interactive diagram illustrating the optimization of the new operation skill process based on user feedback. Figure 6 This is a flowchart illustrating an operational skills management method applied to a government affairs business scenario according to an embodiment of the present invention; Figure 7 This is a schematic diagram of the main modules of an operation skill management device according to an embodiment of the present invention; Figure 8 This is an exemplary system architecture diagram in which embodiments of the present invention can be applied; Figure 9 This is a schematic diagram of the structure of a computer system suitable for implementing the embodiments of the present invention, such as a mobile device or server. Detailed Implementation

[0013] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0014] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0015] Where there is no conflict, the embodiments and features in the embodiments of this invention can be combined with each other. The acquisition, transmission, storage, use, and processing of data in the technical solutions of this invention comply with the relevant provisions of national laws and regulations, are used for legal and reasonable purposes, and are not shared, disclosed, or sold outside of these legal uses, and are subject to supervision and management by regulatory authorities.

[0016] Regarding user information, necessary measures should be taken to prevent unauthorized access to such personal information data, ensure that personnel authorized to access such data comply with relevant laws and regulations, and safeguard the security of user personal information. Once this user personal information data is no longer needed, risks should be minimized by restricting or even prohibiting data collection and / or deleting the data. Where applicable, including in certain relevant applications, user privacy should be protected through data de-identification, such as by removing specific identifiers (e.g., date of birth), controlling the amount or specificity of stored data (e.g., collecting location data at the city level rather than the specific address level), controlling how data is stored, and / or other de-identification methods.

[0017] The core pain point facing the current digital transformation of government affairs lies in the difficulty of scaling up complex business processes that heavily rely on personal experience. In government business scenarios, many key operations (such as verification of administrative approval materials, cross-departmental data cooperation, and processing of licenses for specific industries) typically require business personnel to master through years of practice. This operational experience often exists only in the minds of senior business personnel or is fragmented through unstructured documents (such as text materials), lacking a systematic mechanism for accumulation and reuse.

[0018] With the rapid development of Large Language Model (LLM) and AI (Artificial Intelligence) agent technologies, modern systems possess powerful natural language understanding and common-sense reasoning capabilities. Simultaneously, the rise of automation technologies (such as OpenClaw) enables AI agents to simulate human actions in local environments to complete complex tasks. Agent Skills technologies (such as the framework proposed by Anthropic) further solidify professional knowledge and workflow specifications into reusable modular assets, enabling the dynamic loading and combination of skills through a progressive disclosure mechanism. OpenClaw, in particular, is a production-grade AI agent runtime platform that supports system command execution, file operations, multi-agent collaboration, and other functions, and can run in a local environment. An agent is an AI entity capable of perceiving its environment, making decisions, and performing actions. Existing technologies provide the following solutions: Option 1: Traditional Customized Business System Solution. Currently, the government sector primarily uses customized business systems (such as ERP (Enterprise Resource Planning), OA, and dedicated approval platforms) to solidify processes. This requires professional developers to design and code the system based on business needs, business experts to convey their experience through written materials or verbal descriptions, and end users to complete business processes by learning the system's interface. The main disadvantages of this solution are as follows: 1. Distortion and inefficiency in experience transfer. The "written materials or verbal descriptions" provided by business experts are insufficient to accurately depict the operational details they are accustomed to, leading to discrepancies between the developed system and actual business experience. According to the research report on the development of government intelligent bodies, the traditional model requires extensive manual review for policy text parsing and process compliance assessment, resulting in inefficiency.

[0019] 2. Long development cycle and insufficient flexibility. Customized business systems require a complete software engineering cycle, including requirements analysis, system design, coding development, testing, and deployment, making them difficult to adapt to frequent changes in government policies. When business processes change, the entire development process must be re-executed, resulting in slow response times.

[0020] 3. High user learning costs. Business personnel need to proactively adapt to the system interface, rather than the system adapting to their operating habits, resulting in high training costs. In government scenarios, many senior business personnel are older and face significant difficulties learning new systems, impacting the effectiveness of system rollout.

[0021] Option 2: Anthropic Skill-Creator technical solution. This solution allows users to generate Agent Skills through natural language descriptions. Its core mechanisms include: automatically generating SKILL.md skill files based on natural language descriptions; providing an evaluation framework for skill effectiveness testing; supporting multi-agent parallel testing and A / B comparison; and reducing the false trigger rate of skills through description optimization suggestions. Essentially, this solution belongs to the "description-generated" skill construction paradigm: users must first convert their business experience into textual descriptions, and the system then generates skill logic based on these descriptions. The main drawbacks of this solution are as follows: 1. Reliance on language and text as intermediaries leads to information loss. Skill-Creator requires users to construct skills through natural language descriptions, which necessitates the ability to abstract operational experience into textual descriptions. However, many government operations involve subtle interface interaction details (such as clicking a specific icon in the third row of a table, or waiting for a loading animation to finish before proceeding to the next step). These details are difficult to describe accurately in words, resulting in discrepancies between the generated skills and actual operations.

[0022] 2. Lack of real-time operational verification mechanism. After Skill-Creator generates skills based on descriptions, it lacks a real-time interactive verification process with real business systems. According to Anthropic's design, Skill-Creator only helps in designing and optimizing skills; it cannot perform automated testing or generate quantitative evaluation results. This means that the generated skills may be incompatible with real systems.

[0023] 3. Incomplete skill optimization loop. Existing technologies lack a mechanism for continuously collecting execution feedback and automatically iterating and optimizing skills in real-world usage scenarios. While Skill-Creator supports iterative improvements based on edge cases, it primarily relies on manual identification of problems and proactive triggering of optimizations, rather than the system automatically capturing execution anomalies and recommending optimization solutions.

[0024] See Figure 1 The diagram shows the main flowchart of an operational skills management method provided by an embodiment of the present invention, which includes the following steps: S101: In response to the skill teaching instruction, the operation interface of the business system is activated, and the background monitoring service is started at the same time. The background monitoring service captures the user's operation steps on the operation interface and the feedback information of the business system on the operation steps in real time. Based on the operation steps and the feedback information, an operation log is generated and stored in the monitoring log. S102: Read the latest operation log from the monitoring log of the background monitoring service in real time, parse the operation steps and feedback information in the latest operation log to generate operation step description information; S103: In response to the user's interactive correction operation on the operation step description information, the corrected operation step description information is obtained, and the operation step description information is summarized in order according to the generation order to generate operation skills.

[0025] This implementation describes the process of converting a user's (such as a business person's) operational experience into operational skills. The core process is detailed in the timeline. Figure 2 As shown, in the context of AI agents, an "Operation Skill" represents a modular definition that solidifies professional knowledge and workflow specifications into reusable assets, typically including elements such as execution instructions, triggering conditions, and resource files. This solution can be applied to various scenarios, such as government affairs scenarios, where the AI ​​agent is a government affairs agent, and the generated Operation Skills are government affairs skills.

[0026] This solution can be executed in browsers, applications, and mini-programs, providing an operation entry interface, as shown in Figure 3(a). Users click the "Start Recording" button on the operation entry interface to trigger a skill teaching instruction. The AI ​​agent responds to the skill teaching instruction, identifies the first intent of the instruction, and calls the skill generation module corresponding to that intent to activate the business system's operation interface. Simultaneously, it starts the background monitoring service (which can also start the recording tool). After these preparations are complete, the user is prompted to begin the operation. The AI ​​agent can also display operation guidance information, reminding the user to check the parsed operation step description information after each step. The background monitoring service utilizes technologies including, but not limited to, browser background monitoring, computer vision monitoring, API (Application Programming Interface) monitoring, and system service operation logs; this solution does not impose restrictions on these technologies.

[0027] Users perform specific actions within the user interface, such as clicking buttons, entering data, and page navigation. The background monitoring service captures these actions in real time, along with feedback from the business system, including changes in interface state and data loading results. Based on the captured actions and feedback, the background monitoring service generates and stores operation logs in the monitoring logs.

[0028] The AI ​​agent reads the latest operation logs in real time from the monitoring logs of the backend monitoring service, calls the intelligent engine, and parses the operation steps and feedback information in the latest operation logs to generate operation step description information, which is a summary of the current operation steps. For example, suppose a user performs the "click query button" operation in the business system, and the backend monitoring service captures "the user performs a click event at coordinates (100, 200)" and "the business system displays the query results table, with a loading time of 2 seconds." The operation step description information generated by the AI ​​agent is "click the query button, and the business system returns the query results."

[0029] In one optional implementation, to facilitate users' viewing of the operation step description information parsed in real time by the AI ​​agent, the operation step description information interface can be displayed as a floating window above the operation interface, as shown in Figures 3(b) and 3(c). The "Screen Recording Demonstration" function in both interfaces is enabled. This is merely an example; in practice, other display formats can be used, such as attaching the operation step description information interface as a floating panel to the edge of the operation interface, integrating it into the sidebar area of ​​the operation interface, displaying it as a tab alongside the operation interface, merging it into the status bar of the operation interface, or displaying it as an independent window alongside the operation interface. Regardless of the format, the operation step description information interface must not interfere with the user's normal operation on the operation interface.

[0030] Figure 3(b) shows the operation step description information interface when the background monitoring service is in capture mode, and Figure 3(c) shows the operation step description information interface when the background monitoring service is in paused capture mode. The operation step description information interface is mainly divided into three areas: capture status area, operation key area, and operation step description information area. The capture status area is divided into capture status (such as recording status, with a corresponding recording icon) and paused capture status (such as paused recording status, with a corresponding paused recording icon). The operation key area has a play icon and a finish button. The content of the operation step description information area is updated in real time based on the latest operation step description information. The play icon is divided into a pause button icon and a resume button icon, which need to be dynamically switched according to the user's operation. In addition, during the background monitoring service capture process, the operation step description information interface can also prompt the user to perform the next operation. When the background monitoring service is paused capture, this prompt information will be removed.

[0031] The operation step description information is generated in real time by an intelligent engine, so users can see the AI ​​agent parsing and generating the operation step description information during operation. If the user believes that the AI ​​agent's parsing is inaccurate, they can click the play icon, at which point the play icon on the operation step description information interface will change from a pause button to a resume button. Users can add and correct information to the latest operation step description information area. The AI ​​agent will then correct the latest operation step description information based on the correction information, obtain the adjusted operation step description information, and update the displayed content of the operation step description information interface.

[0032] After the user confirms that the corrected operation step description information is correct, they can click the play icon again. This time, the play icon changes from a continue button to a pause button, triggering the background monitoring service to continue capturing operations. After completing multiple steps involved in the business process on the operation interface, the user can click the complete button shown in Figure 3(b) or Figure 3(c), triggering the background monitoring service to stop capturing operations and notify the AI ​​agent that all operation steps have been completed. At this time, the AI ​​agent summarizes the description information of each operation step according to the generation order of the description information, forms an operation skill, and automatically uploads it to the skill repository for use by other users.

[0033] In one optional implementation, users can manually add breakpoints during the operation to identify key steps in the business process. When the operation process is lengthy, the business system can prompt the user to break down the operation steps to ensure that key nodes are effectively identified and recorded. For example, when a user executes a complex approval process containing 10 steps, the AI ​​agent prompts "A long operation process has been detected; it is recommended to add a breakpoint" after the 5th step. After the user clicks to add a breakpoint, the first 5 steps are marked as one operation unit as "Initial Material Review Stage," and the subsequent 5 steps are marked as another operation unit as "Secondary Material Review Stage," facilitating subsequent skill management and use.

[0034] The operational skills generated through the above process can be directly used by other users without requiring specialized learning. For example, by capturing and parsing the operations of senior approvers, the "Enterprise Qualification Review" skill can be generated. New employees do not need to handle enterprise qualification review operations when processing business; they can directly call the enterprise qualification review skill (the AI ​​agent can take over the user's terminal (such as a personal computer) for systematic operation) to complete the task directly, eliminating the need for new employees to undergo a long period of learning and practice. This method improves business processing efficiency, the AI ​​agent can work 24 / 7, and the time cost of repetitive operations is reduced through skill reuse.

[0035] It is understood that the specific values ​​listed in the above hypothetical description of operational skills management are merely illustrative and not restrictive. In practice, other values ​​can be set according to requirements. Similarly, the specific values ​​listed in subsequent embodiments are also just examples and are not intended to be unique. In addition, the technical types appearing in this solution represent only one type of technology and do not limit the choice of solution.

[0036] The method provided in the above embodiments, by capturing and parsing operation steps in real time, can transform users' operational experience on the user interface into standardized, reusable operational skills. This avoids the loss of experience caused by staff turnover and significantly lowers the threshold for skill transfer, allowing newcomers to quickly master complex business operations without long-term practice. This method improves business processing efficiency by ensuring a high degree of match between the generated operational skills and actual business experience through real-time capture and parsing and user feedback mechanisms, thereby enhancing the accuracy of complex business process execution.

[0037] See Figure 4 The diagram illustrates an optional operational skill management method according to an embodiment of the present invention, comprising the following steps: S401: In response to a business process execution instruction, determine the target operation skill based on the business process execution instruction, and activate the operation interface; S402: Based on the current operation step description information in the target operation skill, perform automated operation in the operation interface; wherein, the current operation step description information is determined based on the list of operation step description information in the target operation skill; S403: In response to an abnormality in the operation process, based on the current operating environment of the business system and the feedback abnormality information, the current operation step description information is corrected, and the automated operation is re-executed in the operation interface based on the corrected operation step description information. S404: In response to the completion of all operation step description information in the target operation skill, the operation step description information is summarized in the order of execution to generate a new operation skill.

[0038] This implementation describes the iterative optimization process of operational skills. Due to the continuous iteration of the business system, some operational steps may change, such as changes in the position of interface elements or adjustments to the operation flow. To address this, this solution includes a skill optimization module to iteratively optimize the Skill based on feedback information from the business system and users. The core process is shown in sequence diagram 5(a).

[0039] For step S401, as shown in Figure 3(a), this solution can also set an execution operation entry interface. Users can click on the "Business Process Execution Option" in the execution operation entry interface to trigger the business process execution instruction. The AI ​​agent responds to the business process execution instruction, identifies the second intent of the business process execution instruction, calls the skill optimization module corresponding to the second intent, determines the corresponding target operation skill according to the skill identifier in the business process execution instruction, and wakes up the operation interface.

[0040] The retrieval of target operational skills can employ techniques such as keyword retrieval, vector retrieval, semantic retrieval, hybrid retrieval, and similarity retrieval; this solution does not impose any restrictions on these methods. Taking similarity retrieval as an example: each operational skill is configured with a skill name (e.g., weekly report generation, data analysis, document collaboration, meeting minutes, etc.) and skill description information. The skill name and skill description information can be user-defined or automatically generated based on the operational step description information. Operational skills in the Skill library are used as candidate operational skills. The first similarity between the target skill name in the business process execution instruction and the skill name of the candidate operational skill is calculated, as well as the second similarity between the target skill description information in the business process execution instruction and the skill description information of the candidate operational skill. Finally, the first and second similarities are summed, averaged, or weighted summed to calculate a comprehensive similarity. The candidate operational skill with the highest comprehensive similarity is selected as the target operational skill.

[0041] For steps S402 and S403, Skill includes a list of operation step description information. The current operation step description information is determined based on the list of operation step description information. The first one is the operation step description information that is ranked first, the second one is the operation step description information that is ranked second, and so on until all operation step description information has been executed.

[0042] The system initiates an operation process and executes automated operations based on the current operation step description in the user interface. If no error message appears during execution, the next operation step description is used as the new current operation step description and executed. If an error message appears during execution, the AI ​​system invokes the intelligent engine to correct the current operation step description based on the error message and the current operating environment of the system. The system then re-executes the automated operation based on the corrected description until no more error messages appear in the user interface.

[0043] For example, when the AI ​​agent executes the operation step "Click the save button", the business system reports an error "Please enter the required field". In response to the business system error, the AI ​​agent detects that a new required field XX has been added to the current operation interface. It then calls the intelligent engine to correct the operation step description from "Click the save button" to "Enter the required field and then click the save button" based on the error information (missing required field) and the current operating environment (new field XX). The AI ​​agent then re-executes the automated operation in the operation interface.

[0044] For step S404, after all operation step descriptions in the operation step description information list have been executed, the AI ​​agent will sequentially summarize and correct the operation step descriptions according to their execution order to generate a new operation skill and store it in the Skill repository. The AI ​​agent can add a preset value to the version number of the target operation skill to obtain the version number of the new operation skill. Furthermore, it can also regenerate the skill name and skill description information of the new operation skill based on user-defined configurations or operation step description information.

[0045] Referring to Figure 5(b), in one optional implementation, after all operation step descriptions in the operation step description information list have been executed, the AI ​​agent will invoke the intelligent engine to generate an operation report based on the execution process and results of each operation step description information, and prompt the user to check the operation report. The user can then verify the completeness and correctness of the corresponding operation steps in the business system based on the operation report. If incomplete or incorrect information is found, the user can provide feedback on the execution process or results to indicate the error location to the AI ​​agent and provide optimization suggestions (including but not limited to deletion, correction, and addition).

[0046] Based on user feedback, the AI ​​agent uses its intelligent engine to optimize the descriptions and workflows of the corresponding steps in a new skill, and then sends the optimized content to the user for confirmation. Furthermore, it can automatically generate skill optimization patches by comparing the execution path of the original skill with the manually corrected path. After all feedback has been addressed and confirmed by the user, the AI ​​agent stores the optimized new skill in the Skill repository.

[0047] The method provided in the above embodiments addresses the situation where changes in the user interface due to iterative optimization of the business system cause the original operational skills to become ineffective. The AI ​​agent executes the operation step descriptions from the original operational skills within the latest user interface. Based on anomalies in the business system and the current operating environment, it continuously corrects the operation step descriptions and re-executes the automated operations. This iterative optimization of the original operational skills through continuous trial and error and the execution of automated operations further enhances the optimization process. During optimization, the AI ​​agent takes over the user terminal to perform automated operations, allowing the user to observe the process in real time. After completion, the AI ​​agent can generate an operation report, enabling the user to assess the correctness and completeness of the operation from a global perspective. This further ensures the reliability and accuracy of the operational skill optimization, resolving the existing problems of "lack of real-time operation verification mechanism" and "incomplete skill optimization closed loop."

[0048] See Figure 6 The diagram illustrates an operational skills management architecture for government affairs scenarios according to an embodiment of the present invention, including the following steps: 1. The government AI intelligent agent responds to skills teaching instructions by calling the skills generation module, and uses the background monitoring service to capture in real time the user's operation steps on the government operation interface and the feedback information of the business system on the operation steps, so as to generate operation logs; 2. Read the latest operation logs in real time from the monitoring logs of the background monitoring service, call the intelligent engine to parse the operation steps and feedback information in the latest operation logs, and generate operation step description information; 3. Receive user-defined configurations or information based on operation steps to obtain the skill name and description of government skills; 4. Summarize the descriptions of each operation step in the order of generation to generate government skills and upload them to the government skills repository; 5. In response to the business process execution instructions, invoke the skill optimization module to determine the target government skills that conform to the business process execution instructions, and perform automated operations in the business operation interface; 6. In response to an anomaly during the operation process, the intelligent engine is invoked to correct the description information of the current operation steps based on the current operating environment of the business system and the feedback anomaly information, and the automated operation is re-executed in the operation interface based on the corrected description information of the operation steps. 7. Once all the operational steps in the target government skill have been executed, summarize the operational step descriptions in the order of execution to generate a new government skill. 8. Summarize the execution process and results of the description information of each operation step in the new government affairs skills to generate an operation report; based on the user's feedback on one or more execution processes and / or results in the operation report, optimize the corresponding operation step description information and / or operation links in the new government affairs skills to obtain the optimized new government affairs skills.

[0049] In summary, this invention provides a method for generating and iteratively optimizing operational skills, which has at least the following advantages compared to existing technologies: 1. Achieving "Zero-Text" Skill Generation Based on Operation Capture: Users do not need to write any descriptive documents. The AI ​​agent automatically generates reusable operational skills simply by capturing normal user actions within the business system's interface through a background monitoring service. This reduces user learning costs, eliminates information loss during the traditional "experience → text description → skill" conversion process, and improves business efficiency and flexibility. Furthermore, this method can transform subtle operational experiences stored only in the mind (such as mouse movement trajectories, timing judgments, and abnormal interface recognition) into structured skill data, solving the problems of fragmented experience, distorted experience transmission, and information loss caused by reliance on language and text as intermediaries.

[0050] 2. Construct a closed-loop operational skill optimization system: By automating the execution of operational skills and using iterative optimization through continuous trial and error and automated execution based on anomaly information from the business system and the current operating environment, operational skills are optimized further. Simultaneously, operational reports are compiled for users to view, and operational skills are further optimized based on user feedback. Therefore, through an iterative optimization mechanism driven by anomaly monitoring and manual correction during execution, a closed-loop optimization system of "execution-monitoring-correction-learning" is established, enabling the continuous evolution and precise inheritance of business experience, and solving the existing problems of lacking real-time operational verification mechanisms and incomplete skill optimization closed loops.

[0051] See Figure 7 The diagram shows the main modules of an operation skill management device 700 provided in an embodiment of the present invention, including: The capture module 701 is used to respond to the skill teaching instruction, wake up the operation interface of the business system, and start the background monitoring service at the same time, so that the background monitoring service captures the user's operation steps on the operation interface in real time, as well as the feedback information of the business system to the operation steps, and generates operation logs based on the operation steps and the feedback information and stores them in the monitoring log. The parsing module 702 is used to read the latest operation log from the monitoring log of the background monitoring service in real time, and parse the operation steps and feedback information in the latest operation log to generate operation step description information. The correction module 703 is used to respond to the user's interactive correction operation on the operation step description information, obtain the corrected operation step description information, and summarize the operation step description information in sequence according to the generation order to generate operation skills.

[0052] The apparatus for implementing this invention further includes an interaction module, used for: The interface displays the operation step description information; wherein, the operation step description information interface includes an operation key area and an operation step description information area, the operation key area is set with a play icon and a complete button, and the operation step description information area is updated in real time based on the latest operation step description information. During the background monitoring service capture process, in response to the user's trigger operation on the play icon, the play icon is set as the continue button icon, and the background monitoring service is triggered to pause the capture in order to receive the user's correction information on the operation step description information in the operation step description information area; If the background monitoring service pauses capture, in response to the user's trigger operation on the play icon, the play icon is set to a pause button icon to trigger the background monitoring service to continue capturing; In response to the user's triggering operation of the completion key, the background monitoring service is triggered to stop capturing, and an operation skill is generated based on the operation step description information in the operation step description information area.

[0053] In the device of this invention, the operation step description information interface is displayed as a floating window overlaid on the operation interface.

[0054] The apparatus for implementing this invention further includes an optimization module, used for: In response to a business process execution instruction, the target operation skill is determined based on the business process execution instruction, and the operation interface is activated. Based on the current operation step description information in the target operation skill, an automated operation is performed in the operation interface; wherein, the current operation step description information is determined based on the list of operation step description information in the target operation skill; In response to an anomaly during the operation process, the current operation step description information is corrected based on the current operating environment of the business system and the feedback anomaly information, and the automated operation is re-executed in the operation interface based on the corrected operation step description information. In response to the completion of all operation step descriptions in the target operation skill, the operation step descriptions are summarized in the order of execution to generate a new operation skill.

[0055] The device for implementing this invention further includes an attribute module, used to: receive user-defined configuration or a list of operation step description information to obtain the skill name and skill description information of the operation skill; The optimization module is used for: Obtain the target skill name and target skill description information included in the business process execution instruction, and determine the candidate skill name and candidate skill description information for each candidate operation skill; Calculate the first similarity between the candidate skill name and the target skill name, and the second similarity between the candidate skill description information and the target skill description information; determine the comprehensive similarity based on the first similarity and the second similarity. The candidate skill with the highest overall similarity will be selected as the target skill.

[0056] In the apparatus of this invention, the optimization module is used for: The execution process and results of each operation step description in the new operation skill are summarized to generate an operation report; Based on user feedback on one or more execution processes and / or execution results in the operation report, the corresponding operation step description information and / or operation chain in the new operation skill are optimized to obtain the optimized new operation skill.

[0057] Furthermore, the specific implementation details of the device described in the embodiments of the present invention have been described in detail in the above-described method, so the details will not be repeated here.

[0058] Figure 8 An exemplary system architecture 800 to which embodiments of the present invention can be applied is shown, including terminal devices 801, 802, 803, network 804, and server 805 (only an example).

[0059] Terminal devices 801, 802, and 803 can be various electronic devices with displays and web browsing capabilities, and can be equipped with various communication client applications. Users can use terminal devices 801, 802, and 803 to interact with server 805 via network 804 to receive or send messages, etc.

[0060] Network 804 is a medium used to provide a communication link between terminal devices 801, 802, 803 and server 805. Network 804 can include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

[0061] Server 805 can be a server providing various services, such as a backend management server supporting shopping websites browsed by users using terminal devices 801, 802, and 803 (this is just an example). The backend management server can analyze and process data such as received product information query requests, and feed back the processing results (such as target push information and product information—this is just an example) to the terminal devices. It should be noted that the method provided in this embodiment of the invention is generally executed by server 805, and correspondingly, the apparatus is generally set in server 805.

[0062] It should be understood that Figure 8 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0063] The following is for reference. Figure 9 It shows a schematic diagram of the structure of a computer system 900 suitable for implementing a terminal device of the present invention. Figure 9 The terminal device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0064] like Figure 9As shown, the computer system 900 includes a central processing unit (CPU) 901, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 902 or programs loaded from storage section 908 into random access memory (RAM) 903. The RAM 903 also stores various programs and data required for the operation of the system 900. The CPU 901, ROM 902, and RAM 903 are interconnected via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0065] The following components are connected to I / O interface 905: an input section 906 including a keyboard, mouse, etc.; an output section 907 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to I / O interface 905 as needed. A removable medium 911, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 910 as needed so that computer programs read from it can be installed into storage section 908 as needed.

[0066] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 909, and / or installed from removable medium 911. When the computer program is executed by central processing unit (CPU) 901, it performs the functions defined above in the system of this invention.

[0067] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0068] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0069] The modules described in the embodiments of the present invention can be implemented in software or hardware. The described modules can also be housed in a processor; for example, a processor may be described as including a capture module, a parsing module, and a correction module. The names of these modules do not necessarily limit the module itself; for example, a correction module may also be described as an "adjustment module."

[0070] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs that, when executed by the device, cause the device to perform any of the above-described operation skill management methods.

[0071] The computer program product of the present invention includes a computer program that, when executed by a processor, implements the operation skill management method in the embodiments of the present invention.

[0072] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for managing operational skills, characterized in that, include: In response to the skills teaching instruction, the operation interface of the business system is activated, and the background monitoring service is started at the same time. The background monitoring service captures the user's operation steps on the operation interface in real time, as well as the feedback information of the business system on the operation steps. Based on the operation steps and the feedback information, an operation log is generated and stored in the monitoring log. The latest operation logs are read in real time from the monitoring logs of the background monitoring service, and the operation steps and feedback information in the latest operation logs are parsed to generate operation step description information. In response to the user's interactive correction of the operation step description information, the corrected operation step description information is obtained, and the operation step description information is summarized in the order of generation to generate operation skills.

2. The method according to claim 1, characterized in that, The method further includes: The interface displays the operation step description information; wherein, the operation step description information interface includes an operation key area and an operation step description information area, the operation key area is set with a play icon and a complete button, and the operation step description information area is updated in real time based on the latest operation step description information. During the background monitoring service capture process, in response to the user's trigger operation on the play icon, the play icon is set as the continue button icon, and the background monitoring service is triggered to pause the capture in order to receive the user's correction information on the operation step description information in the operation step description information area; If the background monitoring service pauses capture, in response to the user's trigger operation on the play icon, the play icon is set to a pause button icon to trigger the background monitoring service to continue capturing; In response to the user's triggering operation of the completion key, the background monitoring service is triggered to stop capturing, and an operation skill is generated based on the operation step description information in the operation step description information area.

3. The method according to claim 2, characterized in that, The operation steps description information interface is displayed as a floating window overlaid on top of the operation interface.

4. The method according to any one of claims 1-3, characterized in that, After generating the operational skill, the method further includes: In response to a business process execution instruction, the target operation skill is determined based on the business process execution instruction, and the operation interface is activated. Based on the current operation step description information in the target operation skill, an automated operation is performed in the operation interface; wherein, the current operation step description information is determined based on the list of operation step description information in the target operation skill; In response to an anomaly during the operation process, the current operation step description information is corrected based on the current operating environment of the business system and the feedback anomaly information, and the automated operation is re-executed in the operation interface based on the corrected operation step description information. In response to the completion of all operation step descriptions in the target operation skill, the operation step descriptions are summarized in the order of execution to generate a new operation skill.

5. The method according to claim 4, characterized in that, After generating the operation skill, the method further includes: receiving user-defined configuration or a list of operation step description information to obtain the skill name and skill description information of the operation skill; The step of determining the target operation skill based on the execution instructions of the business process includes: Obtain the target skill name and target skill description information included in the business process execution instruction, and determine the candidate skill name and candidate skill description information for each candidate operation skill; Calculate the first similarity between the candidate skill name and the target skill name, and the second similarity between the candidate skill description information and the target skill description information; determine the comprehensive similarity based on the first similarity and the second similarity. The candidate skill with the highest overall similarity will be selected as the target skill.

6. The method according to claim 4, characterized in that, The step of sequentially summarizing the description information of each operation step according to the execution order to generate a new operation skill also includes: The execution process and results of each operation step description in the new operation skill are summarized to generate an operation report; Based on user feedback on one or more execution processes and / or execution results in the operation report, the corresponding operation step description information and / or operation chain in the new operation skill are optimized to obtain the optimized new operation skill.

7. An operational skill management device, characterized in that, include: The capture module is used to respond to skill teaching instructions, wake up the operation interface of the business system, and start the background monitoring service at the same time. This allows the background monitoring service to capture the user's operation steps on the operation interface in real time, as well as the feedback information of the business system to the operation steps. Based on the operation steps and the feedback information, it generates operation logs and stores them in the monitoring log. The parsing module is used to read the latest operation logs in real time from the monitoring logs of the background monitoring service, and parse the operation steps and feedback information in the latest operation logs to generate operation step description information. The correction module is used to respond to the user's interactive correction operation on the operation step description information, obtain the corrected operation step description information, and summarize the operation step description information in the order of generation to generate operation skills.

8. An electronic device, characterized in that, include: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-6.

9. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-6.

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