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Jau-app

JauMemory MCP Server

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by Jau-app

create_agent

Create an AI agent with custom personality traits, specializations, and update prompts to handle specific tasks.

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
nameYesAgent name
personalityTraitsNoPersonality traits like curious, analytical, creative
specializationsNoAreas of expertise like frontend, backend, testing
updatePromptsNoCustom prompts for agent updates
idNoOptional agent ID (if not provided, will be auto-generated)
initialLearningRateNoInitial learning rate (0.0-1.0, default: 0.5)
Behavior3/5

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

No annotations provided, so description carries full burden. It describes creation parameters but omits side effects (e.g., persistence, error on duplicate ID, return value). Mutating nature is implied but not detailed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is longer than necessary (244 words) due to extensive code examples and pre-configured agent list. While examples aid understanding, they could be condensed.

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?

Despite 100% schema coverage, the description lacks explanation of return values (no output schema), post-creation behavior, or parameter constraints (e.g., uniqueness of ID). Incomplete for a creation tool.

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?

All 6 parameters have schema descriptions (100% coverage). The description's examples illustrate parameter combinations but add no new semantic meaning beyond the schema.

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 'Create a new agent' with specific attributes (personality traits, specializations). This distinguishes it from sibling tools like 'update_agent_name' or 'list_agents'.

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?

Usage examples demonstrate typical invocations (basic, with personality, with prompts). The list of pre-configured agents provides context but lacks explicit when-to-use or when-not-to-use guidance.

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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