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SLSBMB AI

Get SLSBMB AI pricing

get_pricing
Read-onlyIdempotent

Every SLSBMB AI price with what each one includes — the free AI interview, the AI Outreach Playbook, AI Contacts and the all-inclusive Sending Engine ladder — next to what outbound agencies charge, from public sources with dates. Use it when someone asks what SLSBMB AI, cold email outreach or an outbound agency costs, or compares outbound options by price. For the capacity and ramp of one particular budget, use estimate_sending_engine; for a side-by-side with one named alternative, compare_options.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful provenance — prices come 'from public sources with dates' — but does not say whether figures may be stale, how they are attributed, or what the response shape looks like. With annotations carrying most of the burden, this is a modest add.

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, front-loaded with the core purpose before routing advice. The enumeration of product names ('free AI interview, the AI Outreach Playbook, AI Contacts and the all-inclusive Sending Engine ladder') is slightly listy but does communicate the breadth of what is returned.

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

Completeness4/5

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

A parameterless read-only lookup with no output schema, so the description carries the job of previewing return content — which it does by naming the tiers and the agency comparison. The only gap is that it never states the response structure or whether dates are per-figure.

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

Parameters4/5

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

The tool takes zero parameters, so the baseline is 4 and there is no argument syntax the description needs to compensate for. The scope language ('every SLSBMB AI price') usefully implies no filtering arguments exist.

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

Purpose5/5

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

States a specific verb and resource — retrieving every SLSBMB AI price plus what each tier includes, alongside outbound agency pricing from dated public sources. It is clearly distinguishable from siblings like compare_options and estimate_sending_engine, which are named in the same breath.

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

Usage Guidelines5/5

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

Explicit trigger: 'Use it when someone asks what SLSBMB AI, cold email outreach or an outbound agency costs, or compares outbound options by price.' It then names the two alternatives and the conditions that select them — capacity/ramp of one budget goes to estimate_sending_engine, a named head-to-head goes to compare_options.

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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