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Personas ​

A persona is a reusable identity for your AI agent — combining personality, capabilities, and constraints into a single package.

Think of it as a personality + toolbox. Instead of configuring the same system prompt, model, and tool permissions every time you start a conversation, you bundle them into a persona and reuse it everywhere — in chat, in bots, and in automated workflows.

What's Inside a Persona? ​

Every persona is a configuration object with these building blocks:

PropertyWhat it controls
Name, description, avatar, colorIdentity — how the persona appears in the UI
System promptThe core instructions that shape the agent's personality and behaviour
Preferred modelsWhich AI models to use (primary + fallback list, supports glob patterns like claude-*)
Secondary modelsLighter models used for background tasks like context-map generation and compaction
Allowed toolsScoped tool access — restrict exactly what the agent can do. Use * for full access or list specific tools
MCP serversWhich external integrations (databases, APIs, services) this persona can connect to
Loop strategyHow the agent reasons — react (think → act → observe), sequential, or plan_then_execute
Context map strategyHow workspace context is gathered — general, code, or advanced (LLM-powered semantic analysis)
Prompt templatesReusable Handlebars prompt snippets with optional input schemas, invokable from chat or workflows

Why this matters

Personas turn one-off configuration into reusable, shareable agent profiles. A "Code Reviewer" persona always reviews for security issues. A "Technical Writer" persona always outputs clean Markdown. You configure once and use everywhere — no drift, no forgotten instructions.

Built-in vs Custom Personas ​

HiveMind OS uses a namespace convention to separate system and user personas:

  • system/ — Built-in personas that ship with the app (e.g. system/general). These are bundled into the binary, cannot be deleted, but can be customised or archived.
  • user/ — Personas you create (e.g. user/code-reviewer, user/team/ops/monitor). Full control — edit, archive, or delete at any time.

The default persona, system/general, is a general-purpose agent with access to all tools (*) and the ReAct loop strategy. It's the blank canvas you start with.

How Personas Connect to Everything ​

Personas are the common thread across the three main ways you interact with HiveMind OS:

  • Regular chat — Select a persona from the sidebar before (or during) a conversation. The agent adopts that persona's prompt, tools, and model preferences for the entire session.
  • Bots — Every bot wraps a persona with additional triggers and schedules. The persona defines what the bot can do; the bot defines when it does it.
  • Workflows — The invoke_agent and invoke_prompt steps accept a persona ID, so automated pipelines can call different specialist agents at each stage.

Skills ​

Skills are portable knowledge packs that add domain expertise, procedures, and reference material to a persona. Skills are managed per-persona through the UI (not as a field in the persona configuration). From the persona editor:

  • Click Manage Skills to browse, install, enable, or disable skills for that persona
  • Skills are scoped — a "Kubernetes" skill installed on your DevOps persona won't clutter your Technical Writer persona
  • Skills inherit data classification — a skill marked CONFIDENTIAL elevates the persona's effective classification level

Creating and Managing Personas ​

Click Personas in the sidebar to manage your collection:

  1. Create from scratch — Click New Persona, fill in the fields, and save. Your persona appears under the user/ namespace.
  2. Start from a template — Use an existing persona as a starting point and customise from there.
  3. Archive / Restore — Don't need a persona right now? Archive it to hide it from listings. It stays resolvable so existing bots and workflows that reference it keep working. Restore it any time.
  4. Edit built-ins — Customise any system/ persona. You can always reset it back to factory defaults later.

Example: A Security-Focused Code Reviewer ​

Say you want an agent that only reviews code and always checks for security issues. Here's what that persona looks like:

yaml
id: user/code-reviewer
name: Code Reviewer
description: Security-focused code review specialist
systemPrompt: |
  You are a meticulous code reviewer focused on security.
  Always check for: SQL injection, XSS, auth bypasses, secrets in code.
  Be constructive but thorough.
preferredModels:
  primary: claude-sonnet
allowedTools:
  - filesystem.read
  - filesystem.search
  - web.search
loopStrategy: plan_then_execute

Notice what's not in the allowed tools list — filesystem.write, shell.execute. This persona can read and search, but it can never modify your codebase. That's the power of scoped tool access: you get a specialist agent that is capable but contained.

You could then:

  • Start a chat with this persona to review a PR interactively
  • Wire it into a bot that triggers on new pull requests
  • Call it from a workflow step after your CI build passes

Learn More ​

  • Agentic Loops — Deep dive into ReAct, Sequential, and Plan-then-Execute (plan_then_execute) strategies
  • Bots — How bots wrap personas with triggers and schedules
  • Workflows — Automating multi-step pipelines that invoke personas
  • Tools & MCP — How tool access and MCP servers work

Released under the MIT License.