> ## Documentation Index > Fetch the complete documentation index at: https://developers.techwolf.ai/llms.txt > Use this file to discover all available pages before exploring further. # Visier exports Below we list all export types available for the Visier integration. Each export is delivered as a CSV file with a naming convention of `tw__{YYYYMM}_{YYYYMMDD}.csv`. ### Skill Vocabulary TechWolf syncs data regarding the Skills Vocabulary and your unique Skills Taxonomy to Visier in order to enable insights on Skill Cluster, and Skill (sub) Domain level. The Skill Vocabulary export (`tw_skills_profile_{YYYYMM}_{YYYYMMDD}.csv`) provides an overview of all Skills and their classification within the Taxonomy. The CSV contains one row for every Skill. | Field | Note | | --------------------- | ----------------------------------------------------------------------------------------------------------- | | Snapshot Date | Format: YYYY-MM-DD. | | Skill ID | Uses ID of vocabulary that is enabled. | | Skill Name | Uses Skill name of vocabulary that is enabled. | | Skill Category | Skills Taxonomy Skill Domain if the Skill is in the Skills Taxonomy; else "Skills outside of the Taxonomy". | | Skill Category ID | Skills Taxonomy Skill Domain ID if the Skill is in the Skills Taxonomy; else empty. | | Skill Sub-Category | Skills Taxonomy Skill Subdomain if the Skill is in the Skills Taxonomy; else default TechWolf Skill Domain. | | Skill Sub-Category ID | Skills Taxonomy Skill Subdomain ID if the Skill is in the Skills Taxonomy; else empty. | | Skill Group | Skills Taxonomy Skill Cluster if the Skill is in the Skills Taxonomy; else empty. | | Skill Group ID | Skills Taxonomy Skill Cluster ID if the Skill is in the Skills Taxonomy; else empty. | | Skill Data Source | "TechWolf". | | Skill Description | Uses Skill description of vocabulary that is enabled. | ### Employee Info TechWolf syncs some metadata on the Employee to Visier, including a Job Skill Match Score for each Employee to enable Skill gap related insights. The Employee Info export (`tw_employee_{YYYYMM}_{YYYYMMDD}.csv`) provides an overview of all Employees. The CSV contains one row for every Employee. | Field | Note | | ----------------------------- | --------------------------------------------------------------------------------------------------------------------------------------- | | Snapshot Date | Format: YYYY-MM-DD. | | Employee ID | | | Job ID | The unique ID of the Job the Employee is currently assigned to. Empty when the Employee has no assigned position. | | Low Skill Data | Indicates whether or not the Employee has sufficient qualitative input data to build a Skill profile (and to include in data analysis). | | Current Job Skill Match Score | Indicates the match score of the Employee with their current assigned position. This enables Skill gap related insights. | ### Employee Skills TechWolf syncs all your Employee Skill profiles to Visier. On top of that, we can also sync the Skills these Employees are expected to have based on their current assigned Job, alongside proficiency levels from multiple sources, whether or not these Skills are critical for the Job, the sources from which the Skill was inferred, and whether it was inferred from Employee data. The Employee Skills export (`tw_employee_skills_{YYYYMM}_{YYYYMMDD}.csv`) provides detailed Skill data for every Employee-Skill combination. The CSV contains one row for every Employee-Skill pair. | Field | Note | | --------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Snapshot Date | Format: YYYY-MM-DD. | | Date Recognized | | | Employee ID | | | Job ID | | | Skill ID | | | Employee Skill ID | Format: \[employee\_id]-\[skill\_id]. | | Employee Skill State | "Validated"; "Suggested"; "N/A" if the Skill only exists on the Job side. | | Job Skill State | "Validated"; "Suggested"; "N/A" if the Skill only exists on the Employee side. | | Employee Suggested Skill Level Code | Skill level inferred by TechWolf (numeric value); -1 if no inference was possible or Skill is not applicable. | | Employee Suggested Skill Level Name | Mapped label for the suggested level. | | Employee Self-rated Skill Level Code | Skill level self-rated by the Employee (numeric value); 0 if not set/validated; -1 if Skill is not applicable. | | Employee Self-rated Skill Level Name | Mapped label for the self-rated level. | | Employee Manager-rated Skill Level Code | Skill level rated by a N+1 (numeric value); 0 if not set/validated; -1 if Skill is not applicable. | | Employee Manager-rated Skill Level Name | Mapped label for the manager-rated level. | | Employee Peer-rated Skill Level Code | Skill level rated by a peer (numeric value); 0 if not set/validated; -1 if Skill is not applicable. | | Employee Peer-rated Skill Level Name | Mapped label for the peer-rated level. | | Employee Assessed Skill Level Code | Skill level rated via an assessment tool (numeric value); 0 if not set/validated; -1 if Skill is not applicable. | | Employee Assessed Skill Level Name | Mapped label for the assessed level. | | Employee Acquired Skill Level Code | Final computed Skill level; calculation based on client's preference; -1 if Skill is not applicable. | | Employee Acquired Skill Level Name | Mapped label for the acquired level. | | Job Expected Skill Level Code | Required Skill level for the Job, sourced from the Job's Skill profile. Per-customer setting picks the source: validated (governed Skill level only) or suggested (governed value; falls back to TechWolf-inferred when no governed value is set). -1 if no value is available. | | Job Expected Skill Level Name | Mapped label for the expected level. | | Critical Skill | Whether the Skill is marked as "Critical" for the Job; 2 when critical, else 0. The same per-customer setting that drives Job Expected Skill Level Code picks the source: validated (governed Critical only) or suggested (governed value; falls back to inferred when no governed value is set). | | Sources | Lists the sources from which the Skill was inferred. | | Inferred from Employee Data | Indicates whether the Skill was inferred from Employee data or solely based on validation (feedback). | ### Matching Jobs for Employee TechWolf syncs internal mobility data to Visier. This includes data on which Jobs are best suited for Employees. The simple file shows the matching scores. The Matching Jobs for Employee export (`tw_matching_jobs_{YYYYMM}_{YYYYMMDD}.csv`) provides match scores between Employees and Jobs. The CSV contains one row for every Employee-Job match. | Field | Note | | -------------- | ----------------------------------------------------------------- | | Snapshot Date | Format: YYYY-MM-DD. | | Employee ID | | | Job ID | | | Matching Score | Indicates the match score between the Employee and a certain Job. | Currently supported configurations are: * Set the `score_min_threshold`: only include matches with a score above this threshold, higher values mean stricter matching. * Set the `max_matches_per_entity`: limit how many matching Jobs are shown for each Employee. * Set `exclude_low_data_available_entities`: when set to `true`, Jobs with low data availability are excluded from the matching results. * Set `mapping_filter`: only keep rows where Employee and Job Custom Properties match the configured mapping. * Filters: add custom filters on Custom Properties to further refine the results. ### Matching Jobs for Employee Explained The explained file goes deeper into these matches and shows which Skills are present, covered, or missing. The Matching Jobs for Employee Explained export (`tw_matching_jobs_explained_{YYYYMM}_{YYYYMMDD}.csv`) provides a Skill-level explanation of Employee-Job matches. The CSV contains one row for every Skill in each Employee-Job match. | Field | Note | | ----------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Snapshot Date | Format: YYYY-MM-DD. | | Employee ID | | | Job ID | | | Status | Indicates the status of the match: "present" when the Adjacent Skill ID equals the Skill ID, "covered" when the Adjacent Skill ID does not equal the Skill ID, and "missing" when there is no Adjacent Skill ID. | | Skill ID | Skill that the Job has. | | Adjacent Skill ID | The most similar adjacent Skill that the Employee has; empty if the Skill is missing. | | Adjacency Score | Indicates the adjacency score between the required Skill and the adjacent Skill. | Currently supported configurations are: * Set the `score_min_threshold`: only include matches with a score above this threshold, higher values mean stricter matching. * Set the `max_matches_per_entity`: limit how many matching Jobs are shown for each Employee. * Set `exclude_low_data_available_entities`: when set to `true`, Jobs with low data availability are excluded from the matching results. * Set `mapping_filter`: only keep rows where Employee and Job Custom Properties match the configured mapping. * Filters: add custom filters on Custom Properties to further refine the results. ### Matching Employees for Job Provides matching scores between Jobs and Employees, indicating how well Employees match a given Job's requirements. Uses the same schema as [Matching Jobs for Employee](#matching-jobs-for-employee) but from the Job's perspective. The Matching Employees for Job export (`tw_matching_employees_{YYYYMM}_{YYYYMMDD}.csv`) provides match scores between Jobs and Employees. The CSV contains one row for every Job-Employee match. | Field | Note | | -------------- | ----------------------------------------------------------------- | | Snapshot Date | Format: YYYY-MM-DD. | | Employee ID | | | Job ID | | | Matching Score | Indicates the match score between the Job and a certain Employee. | Currently supported configurations are: * Set the `score_min_threshold`: only include matches with a score above this threshold, higher values mean stricter matching. * Set the `max_matches_per_entity`: limit how many matching Employees are shown for each Job. * Set `exclude_low_data_available_entities`: when set to `true`, Employees with low data availability are excluded from the matching results. * Set `mapping_filter`: only keep rows where Employee and Job Custom Properties match the configured mapping. * Filters: add custom filters on Custom Properties to further refine the results. ### Matching Employees for Job Explained Provides a Skill-level breakdown of Job-Employee matches. Uses the same schema as [Matching Jobs for Employee Explained](#matching-jobs-for-employee-explained) but from the Job's perspective. The Matching Employees for Job Explained export (`tw_matching_employees_explained_{YYYYMM}_{YYYYMMDD}.csv`) provides a Skill-level explanation of Job-Employee matches. The CSV contains one row for every Skill in each Job-Employee match. | Field | Note | | ----------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | Snapshot Date | Format: YYYY-MM-DD. | | Employee ID | | | Job ID | | | Status | Indicates the current status of the match: "present" when the Adjacent Skill ID equals the Skill ID, "covered" when the Adjacent Skill ID does not equal the Skill ID, and "missing" when there is no Adjacent Skill ID. | | Skill ID | Skill that the Job has. | | Adjacent Skill ID | Adjacent Skill in the Employee's Skill profile. | | Adjacency Score | Indicates the adjacency score between the required Skill and the adjacent Skill. | Currently supported configurations are: * Set the `score_min_threshold`: only include matches with a score above this threshold, higher values mean stricter matching. * Set the `max_matches_per_entity`: limit how many matching Employees are shown for each Job. * Set `exclude_low_data_available_entities`: when set to `true`, Employees with low data availability are excluded from the matching results. * Set `mapping_filter`: only keep rows where Employee and Job Custom Properties match the configured mapping. * Filters: add custom filters on Custom Properties to further refine the results. ### Job Info TechWolf syncs data regarding the Jobs and their fields. The Job Info export (`tw_job_info_{YYYYMM}_{YYYYMMDD}.csv`) provides an overview of all Jobs. The CSV contains one row for every Job. | Field | Note | | --------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------- | | Snapshot Date | Format: YYYY-MM-DD. | | Job ID | | | Job Name | | | Job Family | | | Job Family Group | | | Low Data Availability | Indicates whether or not the Job has sufficient qualitative input data to build a Skill profile (and to include in data analysis). | | Active | Indicates whether the Job will be used in internal mobility. It will not be used in matching if it is False. This is useful when a Job is being phased out. | | Last Updated | | ### Job Skills Provides detailed Skill information for each Job, including proficiency levels from different rating sources and the Skill's state. The Job Skills export (`tw_job_skills_{YYYYMM}_{YYYYMMDD}.csv`) provides detailed Skill data for every Job-Skill combination. The CSV contains one row for every Job-Skill pair. | Field | Note | | ---------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Snapshot Date | Format: YYYY-MM-DD. | | Date Recognized | | | Job ID | | | Skill ID | | | Job Skill ID | Format: \[job\_id]-\[skill\_id]. | | Job Skill State | "Validated"; "Suggested". | | Job Suggested Skill Level Code | Skill level inferred by TechWolf (numeric value); -1 if no inference was possible. | | Job Suggested Skill Level Name | Mapped label for the suggested level. | | Job Validated Skill Level Code | Skill level validated in the TechWolf Console; 0 if not validated. | | Job Validated Skill Level Name | Mapped label for the validated level. | | Job Expected Skill Level Code | Required Skill level for the Job. Per-customer setting picks the source: validated (governed Skill level only) or suggested (governed value; falls back to TechWolf-inferred when no governed value is set). -1 if no value is available. | | Job Expected Skill Level Name | Mapped label for the expected level. | | Job Validated Critical Skill Value | Whether the Skill is marked as "Critical" for the Job based on the governed (validated) value; 2 when critical, else 0. | | Job Suggested Critical Skill Value | Whether the Skill is inferred as "Critical" for the Job by TechWolf; 2 when critical, else 0. | ### Work Intelligence exports The following exports are only available when the Work Intelligence feature is enabled. They provide Task-level data for Jobs, including AI impact metrics. #### Task Info Master table containing unique Task information, including Task hierarchy and AI impact classification. The Task Info export (`tw_task_info_{YYYYMM}_{YYYYMMDD}.csv`) provides an overview of all Tasks. The CSV contains one row per unique Task across all Jobs. | Field | Note | | ------------------- | ------------------------------------------------------------------------------------------- | | Snapshot Date | Format: YYYY-MM-DD. | | Task | Raw Task description as identified in Job. | | Task ID | Unique identifier for the Task. | | Canonical Task | Standardized/canonical version of the Task (level 4); empty is labeled as "Not Classified". | | Cluster | Task Cluster in hierarchy (level 3); empty is labeled as "Not Classified". | | Subdomain | Task Subdomain in hierarchy (level 2); empty is labeled as "Not Classified". | | Domain | Task Domain in hierarchy (level 1); empty is labeled as "Not Classified". | | AI Impact | AI impact classification: "automatable", "augmentable", or "human". | | HAS\_level | HAS (Human-AI Spectrum) level: "H1", "H2", "H3", "H4", or "H5". | | AI Impact Rationale | Explanation for the AI impact classification. | | task\_source | Origin of the Task: `vocabulary` (work taxonomy) or `custom` (tenant-authored). | #### Job Task Junction table linking Jobs to their constituent Tasks with time allocation. The Job Task export (`tw_job_task_{YYYYMM}_{YYYYMMDD}.csv`) provides the relationship between Jobs and Tasks. The CSV contains one row per Job-Task relationship. | Field | Note | | ---------------- | ---------------------------------------------------------------------------------- | | Snapshot Date | Format: YYYY-MM-DD. | | Job ID | External identifier for the Job. | | Job Title | Title of the Job. | | Task | Raw Task description. | | Task ID | Unique identifier for the Task (FK to Task Info). | | Weekly Hours | Number of hours per week spent on this Task. | | Validation State | Validation state in the governance cycle: "suggested", "rejected", or "validated". | #### Job Task Skill Junction table linking Jobs and Tasks to the Skills required to perform them. The Job Task Skill export (`tw_job_task_skill_{YYYYMM}_{YYYYMMDD}.csv`) provides the Skills linked to each Job-Task combination. The CSV contains one row per Job-Task-Skill relationship. | Field | Note | | ---------------- | ---------------------------------------------------------------------------------- | | Snapshot Date | Format: YYYY-MM-DD. | | Job ID | External identifier for the Job. | | Job Title | Title of the Job. | | Task | Raw Task description. | | Task ID | Unique identifier for the Task (FK to Task Info). | | Linked Skills ID | Unique identifier for the Skill. | | Linked Skills | Name of the Skill. | | Validation State | Validation state in the governance cycle: "suggested", "rejected", or "validated". | #### Job Info (Work Intelligence) Master table containing Job metadata and aggregated AI impact metrics. The Job Info Work Intelligence export (`tw_job_info_wi_{YYYYMM}_{YYYYMMDD}.csv`) provides Job data enriched with AI impact scores. The CSV contains one row per unique Job. Business rules: * `augmentable` + `automatable` + `human` = 1.00 (always sum to exactly 1.00). * Proportions are calculated by weighting Task-level AI impact by `weekly_hours`. * Overall potential is the category with the highest proportion. | Field | Note | | --------------------- | ---------------------------------------------------------------------------------- | | Snapshot Date | Format: YYYY-MM-DD. | | Job ID | External identifier for the Job. | | Job Name | Title/name of the Job. | | Job Family | Job Family classification. | | Job Family Group | Job Family Group classification. | | Augmentable | Proportion of Job that is augmentable by AI (decimal, 0.00-1.00). | | Automatable | Proportion of Job that is automatable by AI (decimal, 0.00-1.00). | | Human | Proportion of Job requiring human-only work (decimal, 0.00-1.00). | | Overall potential | Dominant AI impact category for the Job: "augmentable", "automatable", or "human". | | Low Data Availability | Flag indicating low data quality for this Job. | | Active | Whether the Job is currently active. | | Last Updated | Date Job information was last updated. |