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Rahul D Sarker: Marketing & RevOps Tools

LTV : CAC Ratio Health Grader

ltv_to_cac_ratio_health_grader
Read-onlyIdempotent

Grade the LTV:CAC ratio on a gross-margin basis against health bands, from losing money to under-investing. See the full version at https://rahuldsarker.co/calculators/ltv-to-cac-ratio-health-grader

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cacYesFully-loaded customer acquisition cost
ltvYesCustomer LTV (revenue basis)
grossMarginPctYesGross margin, as a percentage, applied to LTV

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, idempotentHint, non-destructive, and closed-world. The description adds some behavioral context by specifying the gross-margin basis and the range of health bands, but it does not describe the return format, authentication needs, or any rate limits. With annotations covering safety, a 3 is appropriate.

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?

The description is two sentences and front-loads the core purpose. The second sentence is a promotional link to an external calculator, which is arguably extraneous for an agent but does not detract much from the overall brevity.

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?

Given three required numeric parameters and no output schema, the description should ideally explain what the graded result looks like (e.g., a band label, numeric score, or category). It implies a grade against health bands but does not specify the return format or usage context, leaving gaps for an agent to call it correctly.

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%, so the schema fully documents the three parameters. The description mentions 'gross-margin basis' which maps to grossMarginPct, but adds no syntactic or format details beyond what the schema already provides. Baseline 3 is correct when the schema carries the load.

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 uses a specific verb ('Grade') and resource ('LTV:CAC ratio'), and clarifies the basis ('gross-margin') and the output framing ('health bands, from losing money to under-investing'). However, it does not explicitly contrast itself with sibling tools like ltv_cac_calculator, leaving the agent to infer the distinction from the name alone.

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?

The description states what the tool does but gives no guidance on when or why to choose it over alternatives such as ltv_cac_calculator or cac_payback_period_matrix. There are no prerequisites, exclusions, or usage contexts provided.

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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