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BACH-AI-Tools

Open Ai21 MCP Server

question

Answer questions based on provided contexts using advanced natural language processing. Generate accurate answers for virtual assistants, knowledge bases, and more.

Instructions

Our Context-Based Question Answering API provides a robust solution for answering questions based on given contexts or passages. By utilizing advanced natural language processing techniques, our API can understand the nuances of the context and accurately generate relevant answers to user queries. Whether you're building a virtual assistant, a knowledge base system, or any application that requires intelligent question answering, our API can assist you. Integrate our Context-Based Question An...

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations exist; description fails to disclose how the tool receives input (the schema is empty) or what it returns. No mention of auth, rate limits, or edge cases.

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

Conciseness2/5

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

Description is verbose, repetitive, and truncated mid-sentence. It uses marketing fluff without adding substantive info.

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

Completeness1/5

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

No output schema and incomplete description. Missing essential info on return values, error handling, or how to provide inputs. Tool is unusable as defined.

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

Parameters1/5

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

Input schema has zero parameters, yet the description implies the tool takes a question and context. Schema coverage is 100% only because empty, but description adds no parameter details.

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

Purpose2/5

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

Description mentions 'context-based question answering' but is vague and cut off. It does not distinguish from siblings like 'chat' or 'summarization_chatgpt', all of which handle text generation.

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?

No guidance on when to use this tool versus alternatives. Description is generic and does not specify use cases or exclusions.

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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