Skip to main content
Glama
Sign In
curate-ipsum

curate-ipsum

by egoughnour
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

rag_search_tool

Search a RAG vector store to find code relevant to a query. Optionally expand results using the project's call graph.

Instructions

Search the RAG vector store for code relevant to a query. Optionally expands results using the project's call graph.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "rag_search_tool"
  }
}

Input Schema

NameRequiredDescriptionDefault
topKNo
queryYes
projectIdNodefault
collectionNocode_nodes
workingDirectoryNo
useGraphExpansionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.5.1

TDQS

B3.3/5.0
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 of behavioral disclosure. It discloses the core read-only search behavior and the optional graph expansion, but does not detail output format, cost, or side effects. This is minimal but not misleading.

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 primary action, and contains no filler. Every word earns its place, making it appropriately concise.

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?

Given six parameters, no output schema, and no annotations, the description is insufficient. It doesn't explain return values or the meaning of key parameters, and the graph expansion behavior is only vaguely described.

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?

Schema description coverage is 0%, and the description adds no explanation for any of the six parameters. It only mentions 'query' implicitly, while properties like topK, projectId, collection, workingDirectory, and useGraphExpansion remain unexplained.

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's function: searching the RAG vector store for code relevant to a query. It also mentions the optional call graph expansion, which distinguishes it from sibling tools like rag_stats_tool and rag_index_nodes_tool.

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 the tool is for finding relevant code via vector search, but provides no explicit guidance on when to choose this over alternatives like graph_query_tool or query_reachability. It doesn't state exclusions or alternatives, leaving usage inference to the agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools