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list_indexes

List all local knowledge indexes for retrieval-augmented generation. Enables management and review of indexes stored locally without cloud dependencies.

Instructions

List all local knowledge indexes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • Registration of the 'list_indexes' tool via @mcp.tool decorator, delegating to kn.list_indexes().
    @mcp.tool(
        name="list_indexes",
        description="List all local knowledge indexes.",
    )
    def list_indexes() -> list[dict[str, Any]]:
        return kn.list_indexes()
  • Handler function for list_indexes tool, returns kn.list_indexes().
    def list_indexes() -> list[dict[str, Any]]:
        return kn.list_indexes()
  • Core implementation of list_indexes() - iterates _indexes dict and returns list of dicts with name, embed_model, and document_count.
    def list_indexes() -> list[dict[str, Any]]:
        return [
            {"name": n, "embed_model": i.embed_model, "document_count": len(i.documents)}
            for n, i in _indexes.items()
        ]
Behavior2/5

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

No annotations exist, so description carries full burden. It only states the action (list) without revealing traits like whether it shows metadata, requires authentication, or has any side effects.

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?

One short, front-loaded sentence with zero wasted words.

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?

Simple tool with no parameters and existing output schema, but description lacks details about what 'indexes' includes (e.g., names, types). Adequate but minimal.

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?

No parameters in schema, so baseline is 4. Description adds no param info, but none is needed.

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 'List all local knowledge indexes' uses a specific verb (List) and resource (local knowledge indexes), clearly distinguishing from sibling tools like create_index, delete_index, and query_knowledge.

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 (e.g., when to list vs query). It simply states what it does without context 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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