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Shruti Kaushik: Founder GTM Research

Founder-led AI visibility service

founder_ai_visibility
Read-only

How Shruti Kaushik gets a founder and company named in ChatGPT, Perplexity and Google AI answers: the method, the three service tiers, the monthly report, and how to get a free baseline check.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

C2.8/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered, but the description adds no behavioral context of its own — no return format, no indication of whether this returns a page, structured data, or a summary. It only restates content scope.

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

Conciseness3/5

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

It is a single sentence, but a comma-heavy one that front-loads a proper name rather than the tool's action, and the trailing content list is somewhat padded. It is not wasteful, but it is not optimally structured for agent scanning.

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 and no parameters, the description carries the burden of telling the agent what comes back. It lists content topics, which is partial compensation, but gives no sense of the response shape or depth for a knowledge-retrieval tool.

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 schema requires no explanation and there is nothing for the description to disambiguate. Baseline 4 applies per the no-parameter rule.

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

Purpose3/5

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

The description identifies the resource being served (a page about Shruti Kaushik's founder-led AI visibility service) and enumerates its contents: the method, three tiers, monthly report, and baseline check. However, it never states a verb or what the tool actually returns — it reads as a content blurb rather than a tool action, and differentiation from the sibling about_shruti_kaushik is only implicit in the topic.

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 guidance on when to call this tool versus siblings like get_guide, list_topics, or about_shruti_kaushik, nor any exclusions or prerequisites. 'How to get a free baseline check' hints at a user goal but does not translate into a usage condition.

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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