Routing Logic

Use when defining or adjusting marketing-to-sales assignment rules.

Published by @gtmagents·from gtmagents/gtm-agents·0 agent reads / 30d·0 saves·Updated June 14, 2026

Routing Logic Blueprint Skill

When to Use

Designing new lead assignment models (round-robin, territory, pod-based).
Troubleshooting misrouted or unassigned leads.
Simulating capacity scenarios before changing SLAs.

Framework

Qualification Criteria – map scoring thresholds, enrichment fields, and required consent.
Owner Model – hierarchy (account owner, named AE, SDR pod), fallback logic, and tie-breakers.
Capacity Modeling – lead volume forecasts vs available headcount, backlog thresholds.
Automation Flow – MAP/CRM steps, dedupe rules, webhook/API dependencies.
Monitoring & Audits – logging, reconciliation jobs, sample QA cadence.

Templates

Routing matrix (segment → owner → conditions → escalation).
Capacity calculator (leads/day vs SLA vs reps).
QA checklist for automation updates.

Tips

Keep logic declarative (YAML/JSON) for easier audits and version control.
Add synthetic leads to test every path before go-live.
Coordinate with data enrichment to ensure required fields populate upstream.

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Sharebench · Public bench

Connect via MCP.

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1Pick your tool

# Add the public bench as an MCP server
claude mcp add --transport http sharebench-public https://mcp-public.sharebench.ai

# Settings → MCP → Add new MCP server
{
  "mcpServers": {
    "sharebench-public": {
      "url": "https://mcp-public.sharebench.ai"
    }
  }
}

# Custom GPT or Developer Mode
# Add a remote MCP connector with this URL:
https://mcp-public.sharebench.ai

# Append to ~/.codex/config.toml
[mcp_servers.sharebench_public]
url = "https://mcp-public.sharebench.ai"

2Ask your agent for an artifact

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