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elad12390

Web Research Assistant

by elad12390

compare_tech

Compare technologies like frameworks, libraries, databases, or programming languages side-by-side. Automatically gather structured information to support informed decision-making.

Instructions

Compare multiple technologies, frameworks, or libraries side-by-side.

Automatically gathers information about each technology and presents
a structured comparison to help make informed decisions.

Categories:
- "framework": Web frameworks (React, Vue, Angular, etc.)
- "library": JavaScript/Python/etc. libraries
- "database": Databases (PostgreSQL, MongoDB, etc.)
- "language": Programming languages (Python, Go, Rust, etc.)
- "tool": Build tools, CLIs, etc. (Webpack, Vite, etc.)
- "auto": Auto-detect category

Examples:
- compare_tech(["React", "Vue", "Svelte"], reasoning="Choose framework for new project")
- compare_tech(["PostgreSQL", "MongoDB"], category="database", reasoning="Database for user data")
- compare_tech(["FastAPI", "Flask"], aspects=["performance", "learning_curve"], reasoning="Python web framework")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
technologiesYes
reasoningYes
categoryNoauto
aspectsNo
max_results_per_techNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description must cover behavioral traits. It mentions automated information gathering and structured output, but lacks details on read-only behavior, rate limits, or reliability of auto-detection. It does not contradict any annotations, so no contradiction.

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, well-structured with a purpose statement, category list, and clear examples. Every sentence adds value without redundancy, making it easy for an AI agent to parse.

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 complexity with 5 parameters, the description covers the essential aspects: purpose, categories, and usage examples. It omits explanation of 'max_results_per_tech', but since an output schema exists, return values are not required. Overall, it provides sufficient context for correct invocation.

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?

Schema description coverage is 0%, so the description must add meaning. It explains the 'category' parameter with an enum list and provides examples showing usage of 'technologies', 'reasoning', 'aspects'. However, 'max_results_per_tech' is not described, leaving a gap.

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 it compares multiple technologies with specific verb 'Compare' and resource 'technologies, frameworks, or libraries'. It lists categories and examples, differentiating it from sibling tools that perform other tasks like crawling or searching.

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 categories and examples demonstrating when to use the tool. It does not explicitly state when not to use it or alternatives, but the sibling tools are functionally distinct, making misuse unlikely.

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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