Claude-skill-registry decision-trees

Use when designing branching logic, eligibility rules, and fallback paths.

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/decision-trees" ~/.claude/skills/majiayu000-claude-skill-registry-decision-trees && rm -rf "$T"
manifest: skills/data/decision-trees/SKILL.md
source content

Personalization Decision Trees Skill

When to Use

  • Planning logic for dynamic experiences across web, in-app, email, or sales plays.
  • Auditing existing decision flows for complexity, coverage, or compliance gaps.
  • Simulating new branches before deploying rule or model updates.

Framework

  1. Objective Mapping – tie each node to business KPIs and user intents.
  2. Signal Hierarchy – prioritize deterministic signals (consent, account tier, lifecycle) before behavioral or predictive ones.
  3. Fallback Design – ensure every branch has a safe default when data is missing or risk flags appear.
  4. Experiment Hooks – embed test slots at key decision points with guardrail metrics.
  5. Monitoring – log path selections, success rates, and anomaly alerts for continuous tuning.

Templates

  • Decision tree canvas (node, condition, action, fallback, owner).
  • Signal priority matrix (signal → freshness → reliability → privacy risk).
  • Simulation checklist (scenarios, expected path, validation steps).

Tips

  • Keep trees shallow where possible; offload complexity to scoring models or external services.
  • Version control decision logic alongside content assets for traceability.
  • Pair with
    governance
    skill to log approvals for high-impact branches.