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Suggestions

  1. Scheduled trigger: We send out suggestions at specific time intervals. On such an interval cycle, we trigger the TechWolf Teams Bot Backend. The interval can be changed depending on your needs, but usually we send suggestions daily. This might seem like a lot, but this is only the first few days, when the integration kicks off; after the initial period, suggestions will slow down anyways (you probably do not have infinite skills).

  2. Fetch suggestions: To get those suggestions, we fetch them from our own API. More specifically, from the Suggestions Skill Profile endpoint, for all employees.
    We also fetch the Custom Properties for all employees, so that we can figure out the Azure ID for them. This way we know how to link Employees in TechWolf with Teams Users.

  3. Filter employees:

    For each employee that did not validate their previous card we do one of the following:

    • If it was ignored longer than the configured time-period, the previous suggestions are closed. We send suggestions again, with a message indicating that it is a reminder.
    • If it was more recent, we skip suggestions for them, until the next cycle.

    Filter suggestions:

    • For each Skill Cluster, we suggest a maximum number of skills (4 by default). This keeps the variety of the suggestions high. If a Skill Cluster is selected for skill suggestions, we take the maximum number of skills, unless there is less available in the cluster.
    • Enough skill clusters are gathered to reach a minimum number of skills (10 by default).

  4. Send suggestions: We send out the suggestions to the azure service.

  5. Azure to Teams: The azure service sends them to the correct Teams environment, and the employees receive their suggestions.

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Validations

  1. The user submits a card, which informs the bot service that it should send an update to the configured endpoint, which is the TechWolf bot backend.

  2. The message is received by the bot backend, which receives a list of confirmed and rejected skills with their Clusters.

  3. The TechWolf bot stores this information, such as which skills, but also when and by whom (might be different from the subject employee).

  4. The feedback is sent to the TechWolf API, using the Employee Skill Profile feedback endpoint and can be tracked with the source field as "tw-teams-bot". To retrieve these sources in an employee’s profile, use the query parameter &include=sources, which returns the Skill’s source_event with "event_type": "skill_profile_feedback" and "source": "tw-teams-bot".

    If this is enabled, the corresponding Skill Clusters are also marked by their validation status. This information is ready to be used for more downstream applications.

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Employee Skill Management Tab

In addition to our Skill Assistant Bot:

We offer an interactive tab that enables employees to efficiently manage and track their skills. Within this tab, employees can:

  • View and Reevaluate Skills: Access their validated and rejected skills for assessment and potential updates.
  • Add Missing Skills: Identify and add any skills that may be lacking.

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Linking users through Graph

TechWolf will read the Employee ID from the Microsoft Graph API through the following endpoint:

https://graph.microsoft.com/v1.0/users/<user id>?$select=employeeId

Notice the employeeId query parameter to filter out the Employee ID of the given Teams user.

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