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.mdsource 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
- Objective Mapping – tie each node to business KPIs and user intents.
- Signal Hierarchy – prioritize deterministic signals (consent, account tier, lifecycle) before behavioral or predictive ones.
- Fallback Design – ensure every branch has a safe default when data is missing or risk flags appear.
- Experiment Hooks – embed test slots at key decision points with guardrail metrics.
- 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
skill to log approvals for high-impact branches.governance