skills.rest
ajrmooreuk
ajrmooreukCOMMUNITY
Explore all skills by this author →
GitHub

pfc-delta-leverage

Automate DELTA Phase 3 analysis from Phase 2 CGA artifacts into prioritized levers and recommendations.

Updated Feb 17, 2026
Search Tags:#evidence#delta#hypotheses#sensitivity-analysis#prioritisation#logic-tree
One-click install
npx skills add https://github.com/ajrmooreuk/pfi-w4m-dev --skill pfc-delta-leverage
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pfc-delta-leverage
Source: https://github.com/ajrmooreuk/pfi-w4m-dev/tree/main/pfc-core/skills/pfc-delta-leverage
Command: npx skills add https://github.com/ajrmooreuk/pfi-w4m-dev --skill pfc-delta-leverage

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates end-to-end DELTA Phase 3 analysis by loading Phase 2 CGA artifacts, building logic-tree driver models, identifying top levers, and synthesising evidence-backed recommendations.

Core Features & Use Cases

  • Load Phase 2 CGA artifacts from delta-output and extract top-3 gaps, MECE decompositions, evidence, and VSOM alignment.
  • Construct quantitative driver models per gap and identify actionable levers for measurement and intervention.
  • Perform sensitivity analysis and hypothesis formation, test MustBeTrue assumptions, and prioritise recommendations with evidence chains.
  • Generate delta-output artefacts for levers, hypotheses, and recommendations.

Quick Start

Use this skill to run the DELTA Phase 3 workflow against a CGA artifact and produce lever insights with traceable evidence.

Frequently Asked Questions about pfc-delta-leverage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate logic tree analysis for prioritising project gaps?▼

The DELTA Phase 3 workflow requires Phase 2 CGA artifacts from delta-output, extracting top-3 gaps, MECE decompositions, evidence, and VSOM alignment to build driver models and prioritise actionable levers.

What's the best way to perform sensitivity analysis on CGA gap levers?▼

You need Phase 2 CGA artifacts stored in delta-output containing MECE decompositions, evidence, and VSOM alignment. The analysis processes a maximum of three top gaps to produce structured artefacts for levers, hypotheses, and recommendations.

Can I generate evidence-backed recommendations from MECE decompositions?▼

This approach distinguishes itself by applying sensitivity analysis and MustBeTrue assumption testing within quantitative driver models, ensuring recommendations are backed by traceable evidence chains rather than qualitative estimates.

When should I not use automated driver model generation for gap analysis?▼

You should not use automated driver model generation if you lack Phase 2 CGA artifacts in delta-output, or if your project requires analysing more than three top gaps, as the workflow is constrained to a maximum of three gaps.

Related Skills

Explore More Product & Management Skills→
ajrmooreukajrmooreuk

pfc-delta-evaluate

Score current state, define future state, and quantify delta across CGA dimensions.

Community
Advanced
Peter-Swain-IncPeter-Swain-Inc
1

invisible-demand-detector

Detect latent demand signals across five market signal layers.

Official
Advanced
xpert-aixpert-ai
8

scenario-sensitivity-generator

Generate scenario skew, sensitivity, breakpoint, and PM action-threshold analyses for public equity base cases.

Official
Advanced
Likas07Likas07

feedback-synthesizer

Synthesize user feedback from multiple channels into actionable product insights.

Community
Advanced