Skip to main content
Glama

index_code

Index code repositories for AI coding agents to create searchable memory and architecture diagrams. Supports local and remote indexing tiers.

Instructions

Index a code repository (Tier 1 local, Tier 2 via agent)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repo_pathYes
repo_idYes
service_idNo
force_reindexNo
tierNo
batch_sizeNo
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It hints at different indexing methods (local vs. via agent) but doesn't disclose performance characteristics, side effects (e.g., whether indexing is incremental or overwrites existing data), error handling, or authentication needs. The description doesn't contradict annotations, but it's insufficient for a tool with 6 parameters and no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise (one sentence) and front-loaded with the core purpose. However, it's arguably too brief for a complex tool with 6 parameters and no output schema, leaving critical gaps in understanding.

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 the tool's complexity (6 parameters, 0% schema coverage, no output schema, no annotations), the description is incomplete. It doesn't explain what indexing does, what the output looks like, how to interpret results, or handle errors. Sibling tools like 'index_code_continue' suggest ongoing operations, but no context is provided for when to use which.

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 but fails to do so. It mentions 'Tier 1 local, Tier 2 via agent' which loosely relates to the 'tier' parameter but doesn't explain the 6 parameters (repo_path, repo_id, service_id, force_reindex, tier, batch_size) or their interactions. No parameter meanings, formats, or examples are provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool 'Index a code repository' which provides a clear verb ('Index') and resource ('code repository'), but it's vague about what indexing entails and doesn't differentiate from siblings like 'index_code_continue' or 'get_index_job'. The Tier 1/Tier 2 distinction adds some specificity but remains ambiguous without explaining what these tiers mean.

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 explicit guidance on when to use this tool versus alternatives like 'index_code_continue' or 'get_index_job'. The description mentions 'Tier 1 local, Tier 2 via agent' but doesn't explain when to choose which tier or what the 'both' option means. No prerequisites or exclusions are provided.

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/rdanieli/tentra-mcp'

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