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rag_index_nodes_tool

Index code nodes into a RAG vector store for semantic search. Include node ID, text content, and optional metadata to enable retrieval by meaning.

Instructions

Index code nodes into the RAG vector store for semantic search. Each node should have an ID, text content, and optional metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nodesYes
projectIdYes
collectionNocode_nodes
persistDirectoryNo
Behavior2/5

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

No annotations are provided, so the description carries the full burden of disclosing behavioral consequences. It describes an indexing (write/mutation) operation, but does not state whether indexing overwrites existing nodes, whether it is idempotent, requires specific permissions, or how persistDirectory affects behavior. For a mutation tool with zero annotation coverage, this is a significant gap.

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 two sentences, front-loaded with the core action, and the second sentence adds genuinely useful information about node requirements. No wasted words.

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

Completeness2/5

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

The tool has no annotations, no output schema, and 0% schema description coverage, yet the description only covers the basic action and node structure. Missing details like return behavior, failure modes, duplicate handling, and parameter roles leave significant context gaps for an indexing tool.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It explains the structure of the 'nodes' array (ID, text, optional metadata), but does not clarify the meaning of projectId, collection, or persistDirectory. Three of four parameters remain semantically unresolved, which is inadequate for an unannotated tool.

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 uses a specific verb 'Index' with a specific resource 'code nodes into the RAG vector store for semantic search,' clearly differentiating from sibling search/stats tools. It also states node structure (ID, text, optional metadata), further clarifying the tool's purpose.

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 populating the vector store before semantic search, but it does not explicitly state when to choose this tool over alternatives like rag_search_tool, nor does it mention any preconditions or exclusions. This is implied usage rather than explicit guidance.

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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