Skip to main content
Glama

Reindex Project Embeddings

reindex_project
Destructive

Build a semantic index of a project's code by chunking and embedding, enabling code search.

Instructions

Perform deep semantic indexing of a project (code chunking + embeddings) for code search

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_chunksNoMaximum number of chunks to embed (default: 1000)
project_nameYesThe name of the project to reindex
Behavior3/5

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

The annotation already signals destructive behavior via 'destructiveHint: true', so the description is not required to restate that. It adds the process detail of 'code chunking + embeddings', which is useful, but it does not disclose what gets overwritten, potential costs, or side effects beyond what the annotation implies.

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 a single, focused sentence that front-loads the key action ('Perform deep semantic indexing') and includes essential details ('code chunking + embeddings', 'for code search'). Every word contributes to understanding, with no wasted text.

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?

Given the tool's complexity (reindexing, potentially destructive), the description is adequate but lacks guidance on when to use it, what to expect after execution, or any prerequisites. The annotations and schema cover some gaps, but the absence of usage context and output information makes it minimally complete.

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

Parameters3/5

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

The schema description coverage is 100%, and both parameters ('project_name' and 'max_chunks') are clearly documented. The description does not add any further meaning to the parameters, so it meets the baseline without exceeding it.

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 tool performs 'deep semantic indexing' with details on what it involves ('code chunking + embeddings') and the target ('a project'), making the purpose clear. However, it does not explicitly differentiate from the sibling tool 'index_project' beyond the name 'reindex', so it falls short of a 5.

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 'index_project' or 'semantic_code_search'. There is no mention of scenarios, prerequisites, or exclusions, leaving the agent without clear usage context.

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/villagertim/universal-mcp-for-openrouter'

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