Derive auditable business KPIs from verifiable lab data into a structured registry.
npx skills add https://github.com/picmakpro/vibeflow-os --skill kpi-analyst-picmakpro
Please help me install this Agent Skill. Skill: kpi-analyst Source: https://github.com/picmakpro/vibeflow-os/tree/main/plugin/kpi-analyst Command: npx skills add https://github.com/picmakpro/vibeflow-os --skill kpi-analyst-picmakpro
This Skill prevents teams from managing a business with misleading activity counters or invented figures by deriving real KPIs from verifiable lab data and preserving the source behind every value.
Ask the KPI analyst to configure the lab indicators from its brief, validate the proposed schema, create deterministic extractors, and publish the first KPI registry.
High-intent search queries and answers about installing and using this skill.
To derive business KPIs from scattered data without invented metrics, use deterministic extractor scripts that pull verifiable values from lab sources. This ensures every published indicator cites its origin, preventing reliance on meta-level activity counters.
The best way to track revenue and MRR deterministically is by creating repeatable extractor scripts that query source data directly. This bypasses LLM reasoning, ensuring KPI analysis yields verifiable, stable figures for your registry.
Building an auditable KPI registry involves assembling structured data from deterministic extraction, attaching source references and confidence levels to each value. This creates a machine-readable output for dashboard reporting and tracking.
Yes, you need a human-validated stable schema before configuring lead analytics and revenue tracking. Freezing indicator keys after explicit validation ensures deterministic extraction remains repeatable and prevents schema drift.
Yes, you can use jq for deterministic extraction during KPI analysis. It supports governed data acquisition by keeping external data collection human-gated, read-only, and scoped, separating internal extraction from external sources.
KPI analysis fails with misleading activity counters because they lack data provenance and reflect meta-level activity rather than true business metrics. Deriving values from verifiable lab data ensures trustworthy, auditable reporting.
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