What is the primary benefit of using this test bench over testing directly in my CRM?

This skill provides a local Python environment to simulate your CRM routing logic against sample data, allowing you to catch rule overlaps or unrouted leads before they impact live prospects.

What files and resources are included in this purchase?

The purchase includes the core Python simulation script, a structured JSON template for your routing rules, and comprehensive documentation on formatting your lead data and policies.

What are the technical requirements and supported agent environments for this skill?

The skill is compatible with any AI agent that supports Python execution and file management; it requires Python 3.9+ and operates entirely on local CSV/JSON files without needing external API access.

Do I need to connect my Salesforce or HubSpot instance for this to work?

No, this tool is designed for offline auditing and does not require CRM credentials or live connectivity, ensuring your production data remains safe and untouched during the testing phase.

What are the data volume and logic limitations of the simulation engine?

The simulator handles up to 10,000 lead rows and 100 distinct rules, focusing on deterministic logic like exact text and numeric matches rather than fuzzy matching or round-robin rotation.

How does the tool help me identify which specific rules are causing conflicts?

The skill generates a per-row 'trace' report that shows exactly which rule was triggered for every lead, specifically highlighting any rows that resulted in a conflict or failed to route.

Lead Routing Test Bench

Example session with this skill installed

I have a new Northeast territory policy. Test these 50 leads against the rules in territory-rules.txt and tell me if the new rules conflict with the existing Account Executive assignments.

Read your context and instructions
Compiled the lead routing test
Generated the data export

I have completed the simulation for the Northeast territory policy. The local simulator processed 50 leads against 12 rules defined in your policy document.

Lead Routing Simulation Results

Status	Count	Description
ROUTED	42	Successfully matched to a unique destination.
CONFLICT	4	Multiple rules of equal priority matched.
UNROUTED	3	No rules matched and no fallback defined.
KEEP_EXISTING	1	Protected by existing owner policy.

Decision Summary

The simulation identified a priority tie between RULE_NE_04 and RULE_CORP_01 for leads in the "Enterprise" segment. Because both rules carry a priority of 10, the simulator flagged 4 leads for manual review rather than choosing a winner.

Proposed Corrections

Rule ID RULE_NE_04: Increase priority to 5 if the Northeast territory should always override the General Corporate rule.
2.

Missing Data: 3 leads failed to route because the Annual_Revenue field was blank, and your policy lacks a catch-all fallback. Add a fallback destination to handle unknown revenue.

Next steps

Review exceptions.csv to see the specific Lead IDs currently resulting in a CONFLICT.
Update routing-policy.json with the new priority values and rerun the simulation.
Verify the rule-trace.csv for the 3 UNROUTED leads to confirm they meet no other criteria.

exceptions.csv

CSV · data export

Generated

Example file from a real run - the skill writes it into your workspace.

Connects securely to your tools. The creator never sees your data.

About this skill

Two routing rules can both look correct on paper and still compete for the same lead. A blank field can also send a record down the wrong path if it is treated as a failed condition.

Lead Routing Test Bench turns your supplied policy and lead sample into a reproducible local simulation. The included Python tool evaluates the rules under documented semantics and writes results you can review row by row. The agent then explains the observed exceptions and the specific owner decisions needed.

You can see a unique winning rule, an explicit fallback, a protected existing owner, or a visible hold. Equal-priority winners are not resolved by list order. Missing data that could change the winner remains REVIEW. No CRM connection or live assignment is implemented.

This is a focused test bench for rules you can express in the supported schema. It is useful before configuration work, during a routing-policy review, or when checking a representative sample after a proposed policy edit.

How to use

Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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Lead Routing Test Bench