Skip to main content
Glama

ingest_documents

Index workspace documents into vector storage for search and memory. Use during initial setup or to rebuild the entire index from scratch.

Instructions

Index (or re-index) all workspace documents into the vector store. Run this when setting up Tessera for the first time, or when you want to rebuild the entire index from scratch. Optionally pass specific directory paths to index only those.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses that this is a potentially heavy operation ('rebuild the entire index from scratch') and mentions optional directory filtering. However, it lacks details on permissions needed, rate limits, whether it's destructive to existing data, or expected runtime/confirmation behavior.

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?

Three sentences with zero waste: first states core purpose, second gives usage guidelines, third explains parameter usage. Front-loaded with the main action, each sentence earns its place by adding distinct value.

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 1 parameter with no schema descriptions but an output schema exists, the description is reasonably complete. It covers purpose, usage, and parameter intent. However, as a tool that likely performs significant processing, more behavioral context (e.g., idempotency, side effects) would enhance completeness, though the output schema may cover return values.

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?

Parameter count is 1 with 0% schema description coverage. The description adds meaningful semantics: 'Optionally pass specific directory paths to index only those,' explaining that 'paths' parameter controls scoping (full vs. partial indexing). This compensates well for the lack of schema descriptions, though it doesn't specify path format or constraints.

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 verb ('index or re-index') and resource ('all workspace documents into the vector store'), specifying it's for Tessera. It distinguishes from siblings like 'sync_documents' or 'search_documents' by emphasizing full workspace indexing rather than incremental sync or search operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: 'when setting up Tessera for the first time, or when you want to rebuild the entire index from scratch.' Also mentions an alternative usage pattern: 'Optionally pass specific directory paths to index only those,' providing clear context for partial vs. full indexing.

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/besslframework-stack/project-tessera'

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