KPI Tracker

Plan KPI records at company, department, role or individual level with targets and actuals. The skill starts with three to five metrics per level and a fixed review cadence. It builds empty tracking templates rather than calculating results.

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 KPI tracker, target-versus-actual records or a performance metrics spreadsheet. Define units, direction, data sources and reviewers; weighting matters when comparing scores across people.

It does not collect data automatically or connect to a source system. A focused set of regularly reviewed metrics is the recommended starting point, rather than a large unused scorecard. 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 KPI definition, target, actual entry, achievement and review meeting. Its 18 fields are KPI Name, KPI Level, Department, Job Title, Employee Name, Linked OKR, Unit, Direction, Target, Actual, Achievement %, Weight %, Weighted Score, Period, Data Source, Owner, Status and KPI ID. Linked OKR is the relation field. KPI levels are Company, Department, Role and Individual; statuses are Draft, Active, At Risk and Retired. Inputs establish the metric count, target-and-actual shape, units, weighting, review frequency, existing tools and whether a tracker, dashboard or scoring structure is needed.

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_kpi_tracker_status ON kpi_tracker (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.