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SLSBMB AI

About SLSBMB AI

about_slsbmb_ai
Read-onlyIdempotent

What SLSBMB AI is and how it works, step by step: the free AI interview, the AI Outreach Playbook and how deep its research goes, AI Contacts, the managed Sending Engine and the workspace, with results so far, who it serves and the headline prices. Use it when someone asks what SLSBMB AI is, how an AI outbound service works, or whether it fits their outbound sales, fundraising, partnership, hiring, job-search or press outreach. For each price with what it includes, use get_pricing; for what one budget buys, estimate_sending_engine; to weigh SLSBMB AI against another option, compare_options.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile needs no restating. The description adds value by disclosing the content payload (which product areas, results and prices the answer spans) rather than just calling itself an overview. It stops short of saying whether the content is static or how long the answer runs.

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 topic list, then the usage trigger, then the sibling routing. The topic enumeration is long but each item maps to a real section of the answer, so it earns its space; it could be trimmed slightly without loss.

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?

With no parameters, no output schema and full annotation coverage, the description carries the remaining burden well by describing what the answer contains and where to go for narrower questions. Only minor gaps remain: answer length/format and whether the content is fixed or versioned.

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 there is nothing for the description to disambiguate and the baseline is 4. The description correctly implies a parameterless, no-configuration lookup by not mentioning any inputs.

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?

The description states a concrete resource (SLSBMB AI) and enumerates exactly what the tool covers: the free AI interview, the Outreach Playbook, AI Contacts, the Sending Engine, results, audience and headline prices. It also explicitly separates itself from get_pricing, estimate_sending_engine and compare_options, so an agent can pick it without opening the schema.

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?

It gives an explicit trigger ('Use it when someone asks what SLSBMB AI is, how an AI outbound service works, or whether it fits their outbound sales, fundraising, partnership, hiring, job-search or press outreach') and routes three adjacent needs to named siblings. When-to-use, when-to-use-something-else and the alternatives are all present.

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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