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Rahul D Sarker: Marketing & RevOps Tools

Lead Scoring Logic Architect

lead_scoring_logic_architect
Read-onlyIdempotent

Score a lead on weighted fit and behavior criteria and get a routing recommendation (route to sales, nurture, or disqualify). See the full version at https://rahuldsarker.co/calculators/lead-scoring-logic-architect

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
industryFitYesIndustry / ICP match, weight 15
companySizeFitYesCompany size fit, weight 15
titleSeniorityYesJob title / seniority match, weight 10
highIntentActionYesHigh-intent action such as trial or contact, weight 25
pricingPageVisitYesVisited pricing / demo page, weight 20
contentEngagementYesContent / email engagement, weight 15

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safe, repeatable read profile is covered. The description adds genuine behavioral value by disclosing the three-way routing outcome, but it does not describe the returned score, weighting math, or any rate/auth constraints. Adequate, not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with the purpose and outcome front-loaded and no padding. The trailing external link is mildly promotional but takes only a clause.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the return-value burden, and it only partially does so — it names the routing categories but not the numeric score or how weighted inputs aggregate. All six required params are fully self-documented, so an agent can call it, but the response shape remains underspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% — every parameter carries an enum plus an explicit weight (e.g. highIntentAction weight 25, pricingPageVisit weight 20). The description adds nothing beyond that, so the schema already does the heavy lifting and baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb (score) and resource (a lead) plus the distinctive output — a routing recommendation toward sales, nurture, or disqualify. That is far more informative than a name restatement, though it never names or distinguishes itself from close siblings like lead_grading_calculator or lead_quality_intent_evaluator.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use guidance, no prerequisites, and no routing to or away from the many sibling lead-scoring tools. Usage is only inferable from the purpose statement.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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