Skip to main content
Glama

update_persona

Modify existing persona profiles by updating their names and prompt content to adapt AI behavior for different expert roles.

Instructions

기존 페르소나 프로필을 수정합니다

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes수정할 페르소나 이름
contentYes새로운 페르소나 프롬프트 내용

Implementation Reference

  • Handler for update_persona tool: validates input using updatePersonaSchema, saves the updated persona content via savePersona helper, and returns a success message.
    case 'update_persona': {
      const validated = updatePersonaSchema.parse(args);
      await savePersona(validated.name, validated.content);
      return {
        content: [
          {
            type: 'text',
            text: `페르소나 "${validated.name}"이(가) 업데이트되었습니다.`,
          },
        ],
      };
    }
  • Zod schema defining the input structure for update_persona: requires validated name and content fields with size/security constraints.
    export const updatePersonaSchema = z.object({
      name: personaNameSchema,
      content: personaContentSchema,
    });
  • src/index.ts:341-358 (registration)
    Registers the update_persona tool in the MCP server's tool list with name, description, and JSON input schema matching the Zod schema.
    {
      name: 'update_persona',
      description: '기존 페르소나 프로필을 수정합니다',
      inputSchema: {
        type: 'object',
        properties: {
          name: {
            type: 'string',
            description: '수정할 페르소나 이름',
          },
          content: {
            type: 'string',
            description: '새로운 페르소나 프롬프트 내용',
          },
        },
        required: ['name', 'content'],
      },
    },
  • Core helper function that performs security validation on name/content and writes the persona file to the local directory.
    async function savePersona(name: string, content: string): Promise<void> {
      // 파일명 및 컨텐츠 검증
      const validatedName = validatePersonaName(name);
      const validatedContent = validatePersonaContent(content);
    
      const filePath = path.join(PERSONA_DIR, `${validatedName}.txt`);
      await fs.writeFile(filePath, validatedContent, 'utf-8');
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While '수정합니다' implies a mutation operation, it doesn't specify whether this requires specific permissions, what happens to unchanged fields, if changes are reversible, 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 is a single, efficient sentence with zero waste. It's appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration. Every word earns its place, making it highly concise and well-structured.

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 complexity of a mutation tool with no annotations and no output schema, the description is incomplete. It lacks crucial context such as behavioral traits (e.g., permissions, side effects), usage guidelines, and output expectations. The high schema coverage doesn't compensate for these gaps in a tool that modifies data.

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%, meaning the input schema already fully documents both parameters ('name' and 'content'). The description adds no additional meaning beyond what the schema provides, such as explaining parameter interactions or constraints. With high schema coverage, the baseline score of 3 is appropriate.

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 clearly states the action ('수정합니다' - modifies/updates) and the resource ('기존 페르소나 프로필' - existing persona profile), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'create_persona' or 'delete_persona' beyond the 'existing' qualifier, which is why it doesn't reach a perfect 5.

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 an existing persona), exclusions, or comparisons to siblings like 'create_persona' for new personas or 'delete_persona' for removal. This leaves the agent without context for tool selection.

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/seanshin0214/persona-mcp'

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