Gamification Engine

Build an employee points and badges tracker around one behavior worth encouraging. The skill defines award rules, balances and a monthly review before adding a leaderboard. It provides empty data templates for a simple engagement mechanism.

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 to plan employee gamification, an engagement points system or a reward points tracker. Start with one behavior and a monthly reset.

It does not run recognition programs or deliver rewards. A leaderboard is appropriate only when most participants can realistically appear on it. 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.

Inputs identify the behavior, participants, award rules, point values, exclusions and the person awarding points. Choose public or private visibility, points or badges, and whether balances reset monthly. The workflow moves from behavior to point award, balance, leaderboard or summary, and review. Its 11 fields are Player, Employee Name, Department, Points Balance, Points This Month, Level, Badges, Source Module, Last Updated, Notes and Player ID. Level starts with L1 through L5, M1 and M2; there are no specified relation fields.

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 TABLE gamification_engine (
  player VARCHAR(255),
  employee_name VARCHAR(255),
  department VARCHAR(255),
  points_balance NUMERIC NOT NULL,
  points_this_month NUMERIC NOT NULL,
  level VARCHAR(100) NOT NULL,
  badges VARCHAR(255),
  source_module VARCHAR(255),
  last_updated DATE NOT NULL,
  notes TEXT,
  player_id SERIAL PRIMARY KEY,
  created_at TIMESTAMP DEFAULT NOW(),
  updated_at TIMESTAMP DEFAULT NOW()
);

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.