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Aditya201206

AI Competitive Research Assistant (NitroStack MCP)

by Aditya201206

discover_competitors

Identify competitors for a startup or product idea by analyzing its structured properties and keywords. This tool uses search engine APIs to surface relevant competitor profiles for market analysis.

Instructions

Discover relevant competitors for a startup or product idea based on its structured properties and keywords using search engine APIs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ideaNo
problemNo
categoryNo
keywordsNo
geographyNo
valuePropNo
targetUserNo
coreProblemNo
targetAudienceNo
valuePropositionNo
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It mentions using search engine APIs (implying external calls) but does not state whether the tool is read-only, has side effects, requires authentication, or how results are returned. This leaves significant behavioral uncertainty.

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 a single, front-loaded sentence that directly states the tool's purpose. It is efficient and free of fluff, though it omits valuable details that could be included without bloating.

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

Completeness2/5

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

Given 10 parameters, no annotations, and no output schema, the description is too sparse to be complete. It does not explain how parameters relate, what the output looks like, or any edge cases, making it insufficient for an agent to confidently invoke the tool in varied contexts.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It refers to 'structured properties and keywords' generically but does not clarify the 10 parameters, including potentially confusing redundancies like 'valueProp' vs 'valueProposition' and 'targetUser' vs 'targetAudience'. This provides minimal added meaning over the parameter names themselves.

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 clearly states the tool's function: discovering relevant competitors for a startup or product idea. It specifies both the input basis (structured properties and keywords) and the method (search engine APIs), making it distinct from sibling tools like extract_competitor_profiles or compare_competitors.

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 provides no guidance on when to use this tool versus its siblings, such as 'run_competitive_research' or 'market_gap_analysis'. It does not mention exclusions, prerequisites, or which tool to use in different scenarios.

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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