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jefedeoro

JauMemory MCP Server

by jefedeoro

create_agent

Create a new AI agent with defined personality traits and specializations to handle domain-specific tasks within persistent memory sessions.

Instructions

Create a new agent with personality traits and specializations.

Usage Examples: // Basic agent create_agent({ name: "Code Reviewer" })

// Agent with personality create_agent({ name: "Frontend Expert", personalityTraits: ["detail-oriented", "creative", "user-focused"], specializations: ["React", "TypeScript", "CSS", "UX"] })

// Agent with custom prompts create_agent({ name: "Test Engineer", personalityTraits: ["thorough", "systematic"], specializations: ["Jest", "Cypress", "TDD"], updatePrompts: [ "Always consider edge cases", "Write tests before implementing fixes" ] })

Pre-configured Agents (from migration):

  • code-reviewer: Analytical, detail-oriented reviewer

  • backend-dev: Systems thinker for backend development

  • frontend-dev: Creative UI/UX focused developer

  • test-engineer: Quality-focused testing specialist

  • project-manager: Organized project coordinator

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoOptional agent ID (if not provided, will be auto-generated)
nameYesAgent name
updatePromptsNoCustom prompts for agent updates
specializationsNoAreas of expertise like frontend, backend, testing
personalityTraitsNoPersonality traits like curious, analytical, creative
initialLearningRateNoInitial learning rate (0.0-1.0, default: 0.5)
Behavior2/5

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

No annotations are provided, so the description must fully convey behavioral traits. It only states that an agent is created with optional fields, but omits critical details: what happens on success/error, whether names must be unique, how the 'id' auto-generation works, or any side effects. The pre-configured agents list adds migration context but not behavioral specifics.

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 well-structured with a clear summary sentence followed by usage examples and a list of pre-configured agents. The examples are front-loaded and demonstrate parameter usage effectively. It could be slightly more concise by removing the pre-configured list if not essential, but overall it is not overly verbose.

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?

For a creation tool with 6 parameters and no output schema, the description is incomplete. It does not explain what the tool returns after creation (e.g., the created agent object or ID), mention error conditions like duplicate names, or clarify the behavior of optional parameters like 'initialLearningRate'. The pre-configured agents list adds some context but does not cover functional completeness.

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%, so the baseline is 3. The description's usage examples show typical values for parameters like personalityTraits and specializations, marginally adding meaning beyond the schema. However, the schema descriptions are already quite clear, so the description does not significantly enhance parameter understanding.

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 'Create' and the resource 'agent', and specifies that it includes personality traits and specializations. This distinguishes it from siblings like 'list_agents' and 'update_agent_name' by explicitly focusing on creation. Multiple usage examples further reinforce the purpose.

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 does not provide any guidance on when to use this tool versus alternatives like 'update_agent_name' or when not to use it. The examples show usage but do not set context for when creation is appropriate. There is no mention of prerequisites or limitations.

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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