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antonio-mello-ai

idea-reality-mcp

idea_check

Check if a product idea already exists by searching GitHub, Hacker News, npm, PyPI, and Product Hunt. Validate originality before building.

Instructions

Check if a product idea already exists before building it.

Use when users discuss new project ideas, ask about competition, market saturation, or whether something has been built before.

Trigger phrases: "has anyone built", "does this exist", "check competition", "is this idea original", "有沒有人做過", "市場上有類似的嗎", "幫我查這個點子"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idea_textYesNatural-language description of the idea.
depthNo"quick" (GitHub + HN, fast) or "deep" (all sources in parallel).quick

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description must fully disclose behavioral traits. It describes what the tool does (check existence) but does not mention what happens when an idea is found (e.g., how results are presented), whether it modifies data, or any side effects. This lack of detail reduces transparency.

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

Conciseness5/5

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

The description is concise and well-structured: a short main sentence followed by usage guidelines and trigger phrases in a bullet-like format. Every part serves a purpose, and it is front-loaded with the core function.

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?

Given the tool's simplicity (two parameters, no nested objects, output schema present), the description covers most needs. It is missing some behavioral details (e.g., output format) but overall is adequate for an agent to understand the tool's purpose and usage.

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?

The input schema has 100% coverage, so the description adds only minor additional context: it rephrases 'idea_text' as 'natural-language description' and explains the 'depth' enum choices. This is helpful but not essential beyond the schema.

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 that the tool checks if a product idea already exists, with a specific verb ('Check') and resource ('product idea'). It distinguishes itself from any potential siblings by clearly defining its scope, and the trigger phrases further solidify its purpose.

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

Usage Guidelines4/5

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

The description provides explicit guidance on when to use the tool (discussing new projects, competition, market saturation) and includes trigger phrases in multiple languages. However, it lacks explicit 'when not to use' or alternatives, though the context is well-defined.

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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