Skip to main content
Glama

build_deep_index

Build a complete symbol index for code projects to enable code search and analysis. This tool performs full re-indexing and loads it into memory.

Instructions

Build the deep index (full symbol extraction) for the current project.

This performs a complete re-index and loads it into memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • Registration of the 'build_deep_index' MCP tool via @mcp.tool() decorator, with the handler function that delegates to the service.
    @mcp.tool()
    @handle_mcp_tool_errors(return_type='str')
    def build_deep_index(ctx: Context) -> str:
        """
        Build the deep index (full symbol extraction) for the current project.
    
        This performs a complete re-index and loads it into memory.
        """
        return IndexManagementService(ctx).rebuild_deep_index()
  • Handler function that executes the tool logic by calling IndexManagementService.rebuild_deep_index()
    @mcp.tool()
    @handle_mcp_tool_errors(return_type='str')
    def build_deep_index(ctx: Context) -> str:
        """
        Build the deep index (full symbol extraction) for the current project.
    
        This performs a complete re-index and loads it into memory.
        """
        return IndexManagementService(ctx).rebuild_deep_index()
  • Supporting method in IndexManagementService that performs the actual deep index rebuild workflow.
    def rebuild_deep_index(self) -> str:
        """Rebuild the deep index using the original workflow."""
        # Business validation
        self._validate_rebuild_request()
    
        # Deep rebuild via existing workflow
        result = self._execute_rebuild_workflow()
        return self._format_rebuild_result(result)
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context by stating that the tool 'performs a complete re-index and loads it into memory,' which implies it's a resource-intensive operation that updates the index in memory. However, it lacks details on potential side effects, performance impact, or error handling.

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 very concise, consisting of only two sentences that directly state the purpose and key behavioral trait. It is front-loaded with the main action and avoids any redundant or verbose language, making it efficient and easy to parse.

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?

Given the tool's complexity (a re-indexing operation with potential performance implications), the description provides adequate context by explaining what it does and that it loads into memory. With an output schema present, it doesn't need to explain return values. However, it could benefit from more details on when to use it versus siblings or potential risks.

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?

The tool has 0 parameters, and the schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. A baseline score of 4 is given as it handles the lack of parameters correctly without unnecessary information.

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 action ('build') and the resource ('deep index/full symbol extraction for the current project'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'refresh_index' or 'refresh_search_tools', which appear related to indexing operations.

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?

The description provides no guidance on when to use this tool versus alternatives like 'refresh_index' or 'refresh_search_tools'. It mentions that it 'performs a complete re-index,' which might imply it's more comprehensive than other tools, but this is not stated explicitly as a comparison or usage rule.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/johnhuang316/code-index-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server