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raqueljezweb

AnythingLLM MCP Server

by raqueljezweb

create_agent

Create a new AI agent with a custom name, system prompt, and toolset for AnythingLLM workspace automation and task management.

Instructions

Create a new agent

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName of the agent
systemPromptNoSystem prompt for the agent
toolsNoList of tools the agent can use
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states 'Create a new agent' which implies a write/mutation operation, but doesn't disclose behavioral traits such as required permissions, whether creation is idempotent, what happens on failure, or any rate limits. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 'Create a new agent' is extremely concise—three words that directly convey the core action. It's front-loaded with no unnecessary elaboration, making it efficient for quick understanding. Every word earns its place by specifying the verb and resource.

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 (a mutation operation with 3 parameters) and lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions or error handling, and while parameters are documented in the schema, the description adds no context about the creation process or result. For a creation tool, more guidance is needed.

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?

Schema description coverage is 100%, with all parameters (name, systemPrompt, tools) documented in the schema. The description adds no additional meaning beyond the schema, such as explaining parameter interactions or constraints. Baseline is 3 since the schema does the heavy lifting, but no extra value is provided.

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 'Create a new agent' clearly states the action (create) and resource (agent), making the purpose immediately understandable. It distinguishes from siblings like 'update_agent' or 'list_agents' by specifying creation. However, it doesn't specify what type of agent (e.g., AI agent, workspace agent) or domain, leaving some ambiguity compared to more specific descriptions.

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. It doesn't mention prerequisites (e.g., needing system access), when not to use it (e.g., for updating existing agents), or refer to sibling tools like 'update_agent' or 'list_agents' for related operations. Usage is implied by the name but not explicitly stated.

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

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