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Ai decision engine

Skill varunk130/claude-code-skills/skills/product-management/ai-decision-engine

A curated, categorized library of 29 production-grade Claude Code custom skills across finance, product, strategy, game theory, and document processing.

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npx -y skills add varunk130/claude-code-skills --skill ai-decision-engine

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Strategic product decision engine that reads ALL available project context (PRDs, research docs, metrics, competitive intel, roadmaps, CLAUDE.md) and provides holistic, multi-dimensional strategic recommendations. Use when making product prioritization decisions, quarterly planning, evaluating build/ship/kill tradeoffs, resolving conflicting stakeholder input, determining what to build next, or any strategic question requiring synthesis across multiple information sources.

SKILL.md

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PM Decision Engine - Strategic Context Synthesizer

This skill is a strategic reasoning system. It reads ALL available project context, applies multiple frameworks simultaneously, looks for convergence, and produces a recommendation with explicit reasoning chains.

PHASE 1: Context Assembly (Always Do This First)

Before answering ANY strategic question, scan the working directory for:

  • CLAUDE.md or README.md → product context, team info, constraints
  • docs/ or specs/ → existing PRDs, feature specs
  • research/ → user research, interview notes, survey results
  • data/ or metrics/ → analytics exports, dashboards
  • competitive/ → competitor analysis, market research
  • roadmap/ → planning artifacts

For each source found, log:

SourceKey SignalRecencyConfidence
[filename][what it tells us][when updated][high/med/low]

If critical context is missing, say so: "I don't have [X]. My recommendation will be stronger with it."

PHASE 2: Situation Model

Write this out before reasoning:

  • Product stage: Early / Growth / Mature / Turnaround
  • Primary constraint: Engineering capacity / Market timing / Revenue pressure / Tech debt / Competitive threat
  • Active bets: What we're currently building and why
  • Unresolved tensions: Where evidence conflicts
  • Decision type: One-way door (irreversible) vs. Two-way door (reversible)

PHASE 3: Multi-Framework Analysis

Apply ALL FOUR frameworks. Never rely on just one.

Framework 1: Impact x Confidence Matrix

OptionExpected ImpactConfidenceEvidence Sources
[A][quantified if possible][High/Med/Low][which docs]

Framework 2: Strategic Alignment Scoring

Score each option 1-5:

DimensionWeight
User pain severity25%
Business impact (revenue, retention, expansion)25%
Strategic fit (alignment with vision)20%
Timing sensitivity (competitive urgency)15%
Execution feasibility15%

Calculate weighted scores. Show the math.

Framework 3: Second-Order Effects

For top 2-3 options:

  • Direct effect → Second-order effect → Third-order effect
  • Opportunity cost (what gets delayed/killed)
  • Team effect (morale, skills, hiring)
  • Market signal (what this tells customers and competitors)

Framework 4: Pre-Mortem

"It's 6 months from now and this FAILED. What happened?"

  • Failure scenario 1: [specific] - Probability: [%] - Early warning: [signal]
  • Failure scenario 2: [specific] - Probability: [%] - Early warning: [signal]
  • Failure scenario 3: [specific] - Probability: [%] - Early warning: [signal]

PHASE 4: Synthesis & Recommendation

TL;DR: One sentence - what to do and why

Confidence level: High / Medium / Low - because [reason]

Framework convergence:

  • What each framework says
  • Where they agree and disagree
  • What the divergence tells us

The recommendation: 2-3 paragraphs with clear reasoning.

What would change this recommendation:

  1. If we learned [X], we might instead do [Y]
  2. If metric [Z] changes by more than [N%], reconsider
  3. If competitor does [W], reassess

Immediate next steps (this week):

  1. [Specific action]
  2. [Specific action]
  3. [Specific action]

Reasoning Rules

Always:

  • Show reasoning chains
  • Quantify where possible
  • Acknowledge uncertainty with confidence levels
  • Include "do nothing" as an explicit option
  • Separate observation from interpretation

Never:

  • Apply a single framework alone
  • Ignore contradictions between sources
  • Recommend without stating trade-offs
  • Be a yes-machine
  • Forget opportunity cost

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.