okhp3-decision-model-authoringlisted

Author and validate decision models from PNS decision points using DMN-aligned rule tables. Use this skill when the PNS contains three or more gateway decision points that warrant a structured decision table; when the user asks to document business rules as decision logic, build a DMN table, or make decision criteria explicit. This is a recommended extension skill triggered automatically when visual-process-modeling identifies three or more gateways. Produces a decision-model YAML and a human-readable DMN rule table.
OKHP3/skillz · ★ 3 · AI & Automation · score 75

Install: claude install-skill OKHP3/skillz

# okhp3-decision-model-authoring **OverKill Hill P³** · [overkillhill.com](https://overkillhill.com) · [github.com/OKHP3](https://github.com/OKHP3) ## Purpose Transform PNS decision_points into structured DMN-aligned decision models. Each decision point becomes a decision table with explicit input conditions, output values, and the business rule governing the routing logic. --- ## When to use this skill - PNS has **≥3 decision_points** — this is the mandatory trigger condition - User needs a decision table to communicate routing logic to implementers - Business rules are complex enough that prose descriptions are insufficient - Preparing a decision catalog as part of governance documentation ## When NOT to use this skill - PNS has fewer than 3 decision_points — inline the logic in the PNS `decision_points[]` section - Decision logic is trivially binary (yes/no) with no business rule — document in `business_rules[]` instead - Do not model decisions before the PNS is validated (score ≥ 75) --- ## DMN Table Structure Each decision table entry has: | Field | Description | |---|---| | `decision_id` | Stable identifier matching `pns.decision_points[].id` | | `decision_name` | Human-readable label | | `activity_id` | The PNS activity where this decision occurs | | `hit_policy` | `U` (Unique) \| `F` (First) \| `A` (Any) \| `C` (Collect) | | `inputs[]` | Each input: `name`, `type` (string\|number\|boolean), `values[]` | | `outputs[]` | Each output: `name`, `type`, `values[