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query_chroma_db

Query a ChromaDB vector database to retrieve relevant documents using LangChain integration. Specify the persist directory and number of results.

Instructions

Query a ChromaDB vector database using LangChain integration.

Args:
    query: The query string to search for in the vector database.
    persist_directory: Directory path where the vector database is persisted.
    top_k: Number of top results to return (default: 3).

Returns:
    List of retrieved documents with their content and metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
top_kNo
persist_directoryYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It indicates the tool returns a list of documents, implying a read operation, and mentions the LangChain integration. However, it does not explicitly state read-only behavior, prerequisites like an existing persisted DB, or possible side effects, leaving some ambiguity.

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, with an overview, Args, and Returns sections. It includes the default for top_k and avoids filler, ensuring every sentence contributes useful information.

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?

For a simple tool with 3 parameters, no output schema, and no annotations, the description adequately covers purpose, parameters, and return format. It might benefit from noting prerequisites like a pre-existing database or read-only nature, but overall it is sufficiently complete for an agent to invoke it correctly.

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 parameter descriptions in the tool description are essential. Each parameter is explained with meaningful context (e.g., query is the search string, persist_directory is the path, top_k has a default), which goes beyond the raw schema property names and types.

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 queries a ChromaDB vector database using LangChain integration, which is a specific verb+resource pairing. It is distinct from siblings like setup_chroma_db and chroma_db_demo, which are for setup and demonstration respectively.

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

Usage Guidelines3/5

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

The description implies usage for querying an existing vector database but does not explicitly state when to use it over alternatives. No exclusions or alternative tool references are mentioned, making the guidance implicit rather than explicit.

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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