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by sykim52
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Python
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chroma_db_demo

Run a demo to set up ChromaDB with LangChain, index sample texts, and query vector search results.

Instructions

Demonstrate the ChromaDB vector database with LangChain integration.

Args:
    sample_texts: Optional list of sample texts to use for demonstration.
                 If not provided, default sample texts will be used.

Returns:
    Results of setting up and querying the ChromaDB vector database.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "chroma_db_demo"
  }
}

Input Schema

NameRequiredDescriptionDefault
sample_textsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

Without annotations, the description must disclose behavioral traits but only states that it sets up and queries, without detailing side effects, mutability, or return structure. This is insufficient for an agent to anticipate consequences.

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 minimal and well-organized with clear Args and Returns sections. Every sentence contributes value with no redundancy.

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?

The description gives a general overview but lacks specifics about the demonstration output or how it relates to the sibling tools. For a demo tool with no output schema, more detail on expected results would improve completeness.

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?

Although the schema provides no description for the parameter, the tool description explicitly explains sample_texts as an optional list with default fallback behavior, compensating for the low schema coverage. This adds meaningful semantics.

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

Purpose4/5

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

The description clearly states the tool demonstrates ChromaDB with LangChain integration, which is a specific verb-resource pair. However, it doesn't explicitly distinguish itself from sibling tools like setup_chroma_db or query_chroma_db, so it lacks differentiation.

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 is provided on when to use this tool versus the sibling tools. It neither mentions alternatives nor gives context for appropriate usage, leaving the agent to infer.

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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