> ## Documentation Index
> Fetch the complete documentation index at: https://docs.2501.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Specialties

> Configure your agent for specific task domains

Specialties let you specialize agents for specific tasks. Every agent needs a specialty to run. If you don't select one during initialization, it defaults to `SYSOPS`.

## Purpose of Specialties

While 2501 agents are built for autonomous system operations, specialization improves execution accuracy and reliability. Instead of operating generically, specialized agents follow domain-specific guidelines tailored to your infrastructure.

**Example:** An agent with an AWS CLI specialty can manage EC2 instances with specific guidance on CLI usage patterns, error handling, and decision-making logic (like determining appropriate CPU upgrades when asked to "upgrade my sandbox machine").

Specialties work well for:

* Providing context for proprietary or lesser-known tools
* Establishing workflows without full MCP integrations
* Documenting internal conventions and procedures

<Frame caption="Specialties list: each row pairs a display name with a key the CLI and CSV importer use, and shows its mode and scope.">
  <img src="https://mintcdn.com/2501/kr0HtinaCJPsc_vr/images/specialties_list.png?fit=max&auto=format&n=kr0HtinaCJPsc_vr&q=85&s=b0f9206169f96f471e6cfbd4d0305197" alt="Specialties list" width="2880" height="1800" data-path="images/specialties_list.png" />
</Frame>

## Separation of Concerns

To maximize accuracy, use different tools for different purposes:

* **Specialties**: Define workflows, provide context, establish best practices
* **[Operational Rules](/0.7/configure/operational-rules)**: Enforce specific tool usage or behavioral requirements
* **[Blacklist](/0.7/configure/blacklist)**: Prevent execution of prohibited commands

## Managing Specialties

Go to **Command Center** → **Specialties** and click **Create Specialty** to add a new one.

### Name

The display name for your specialty. Use naming conventions that reflect the service domain or agent role.

Example: `TERRAFORM_SPECIALIST`

### Key

A read-only identifier automatically generated from the name. Use this key in CLI commands to assign specialties during agent initialization.

### Description

Optional context about the specialty's purpose and scope.

Example: `Handles Terraform infrastructure files for sandbox environments`

### Scope

A specialty is scoped to either a single organization or the whole tenant. By default it is **scoped to the current organization**, so only that org's agents can use it. Toggle the scope to **tenant** to make it available to all organizations.

### Investigate-Only Mode

A specialty can be pinned to **investigate-only**, meaning any agent using it will always run in read-only mode regardless of what the ticket or gateway requests. This acts as a ceiling: even if a ticket is tagged `@2501:remediate`, agents with an investigate-only specialty will only diagnose and report.

This is useful for safely deploying large fleets of agents (e.g., 1000 Oracle DB agents) where you want read-only analysis by default. You can then selectively enable remediation for specific groups by changing this single setting on the specialty.

When a ticket requested remediation but investigate-only specialties prevented it, the job resolution is flagged as **partial** rather than a failure. See [Agents: Investigate vs Remediate](/0.7/core-concepts/agents#execution-modes-investigate-vs-remediate) for the full priority chain.

### Prompt

The specialty definition itself. Use structured formats like Markdown or XML for clarity.

**Important:** Changes to a specialty immediately affect all agents using it. To test modifications safely, create a new specialty for testing, assign it to a test agent, validate the behavior, then update the production specialty.

For guidance on effective agent prompting, refer to our [Prompting Guide](/0.7/configure/prompting).

## Best Practices

Keep specialty prompts focused and domain-specific. Document expected behaviors and decision criteria with clear examples for complex workflows.

Test specialty changes on isolated agents before rolling them out to production. For critical systems, consider version-controlling your specialty definitions.
