Skip to main content
Glama

brain_list

List all brains in the workspace to discover their IDs. Each brain is a knowledge lens; use scope='all' to reason across all brains.

Instructions

List all brains in the workspace. Use to discover available brains and their IDs. Each brain is a lens on the operator's knowledge — use scope='all' on brain_context to think across all of them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

There are no annotations, so the description itself implies a read-only operation by saying 'List all brains'. It adds context about what each brain is and a pointer to brain_context, which helps the agent understand the domain. It doesn't disclose any side effects or requirements, but for a simple list operation, none are indicated.

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?

Two sentences: the first states the action, the second gives the use case and a cross-reference. Every sentence contributes value, no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the tool's purpose, when to use it, and what to expect (brains and their IDs). It also gives a contextual tip about brain_context with scope='all'. Given no output schema and no parameters, this is sufficient.

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 zero parameters, so parameter semantics are not applicable. The description adds context about discovering IDs and the notion of 'brains as lenses', which gives background, but there are no parameters to document. Baseline 4 for zero-param tools.

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 opens with 'List all brains in the workspace' — a specific verb and resource. It further clarifies the purpose by saying 'Use to discover available brains and their IDs', and distinguishes from siblings by positioning brain_list as the discovery tool while referencing brain_context for cross-brain thinking.

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

Usage Guidelines4/5

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

The description explicitly says 'Use to discover available brains and their IDs', indicating when to use it. It also provides an alternative usage by pointing to 'scope='all' on brain_context to think across all of them'. It doesn't explicitly state when not to use it, but the context is clear enough.

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/ubajxn/saor-mcp'

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