Mentorship Program

Plan internal mentoring records around a stated mentee goal. The skill recommends goal-based matching, session tracking and a closing rating. It creates empty records for mentor-mentee pairs on request.

The skill separates advice, review, conversion and build requests before producing artifacts. Advice receives a short recommendation and an offer of a relevant build. An explicit build request proceeds once essential missing facts are resolved. It asks one question at a time, reuses answers already supplied and stops when further answers would not change the deliverable. Unknown information remains unknown rather than receiving invented values.

Use it for a mentorship programme, mentor matching plan or internal mentoring tracker. Clarify pairs, cross-team participation, programme length, session cadence, matching criteria and approval.

It does not match people automatically or send session reminders. The recommended record follows a meaningful goal rather than a pairing chosen only for convenience. The skill does not calculate payroll, tax, leave balances or KPIs. Automation, reminders and synchronization require an integration layer. Legal, tax and HR review is required before templates drive real decisions.

The workflow is mentee goal, match, sessions, mid review and closing rating. Inputs establish whether matching, session tracking or feedback is needed and how any existing programme operates. Its 16 fields are Mentorship Pair, Department, End Date, Focus Area, Last Session, Mentee Goal, Mentee Name, Mentor Name, Mentorship ID, Next Session, Overall Rating, Progress Notes, Sessions Completed, Sessions Planned, Start Date and Status. Mentee Name and Mentor Name are relation fields. Status options are Proposed, Active, Paused, Completed and Ended. Sessions and the closing rating are the minimal tracking focus, while other fields can support the requested structure.

Requested artifacts can include CSV, SQL DDL, JSON Schema, Notion property mappings or an Excel workbook. The formats derive from one field list: CSV and JSON retain matching display names, while SQL uses normalized identifiers. Dates retain date types, money retains currency types and cross-table references retain relation types. Select options are a starting set that can be renamed to match the business.

One SQL example is:

CREATE INDEX idx_mentorship_program_status ON mentorship_program (status);

Templates are empty by default. Example rows are produced only on request and remain obviously synthetic. Sensitive identifiers should not be repeated unnecessarily during a requested review. Machine-readable data stays separate from explanatory prose and any material validation failures. Excel-compatible CSV uses UTF-8 with a byte order mark and accompanying guidance about number, date and currency columns. An XLSX workbook is a separate requested output rather than a renamed CSV.

The Notion output routes to notion-manual-import for CSV, property mappings, import steps and verification. Manual mappings require no connection. Requested live workspace changes require actual tool access, a verified target and authorization. Imported columns may initially be Text and need their mapped property types applied. Relation links resolve after both relevant databases are imported. A static mapping alone does not establish a completed workspace change.