rasa-building-skills

name	rasa-building-skills
description	Builds skills (capabilities) for a Rasa CALM assistant. Use when the user asks to create, add, or build a skill, capability, or feature for their Rasa assistant.
license	Apache-2.0
metadata	{"author":"rasa","version":"0.1.0","rasa_version":">=3.14.0"}

Building Skills for a Rasa Assistant

Terminology

In Rasa, a skill is a self-contained module inside a Rasa assistant that packages a specific capability or domain (e.g. booking, payments, order tracking).

The term "skill" can also refer to a IDE agent skill (SKILL.md). Use conversation context to determine which meaning the user intends. If ambiguous, ask.

A Rasa skill defines its interface (slots / memory) and logic (flows, prompts, actions, or tools). It is implemented as either:

1. Flow-based — a bundle of flows and slots for guided, deterministic behavior.
2. Sub-agent — a sub-agent that plans and acts autonomously using tools.
3. Hybrid — an orchestrator flow that delegates some steps to a sub-agent.

Workflow

1. Clarify what the user wants the Rasa assistant to do.
2. Choose the implementation approach (see "Choosing the approach").
3. Design the skill boundary — slots, flows, responses, actions, sub-agents (see "Designing the skill boundary").
4. Implement using the appropriate skill:
   • Flow-based → rasa-building-flows
   • ReAct sub-agent → rasa-setting-up-react-agents
   • A2A sub-agent → rasa-setting-up-a2a-agents
5. Ensure the new flows or sub-agents are reachable (via call/link steps or triggerable by their description).

Choosing the approach

The first design choice is how autonomous the skill should be:

if high-risk domain (payments, auth, KYC, PII, compliance):
    use flow-based
elif business logic must be tightly controlled (strict validation, fixed steps):
    use flow-based
elif most steps are deterministic but some need autonomy:
    use hybrid (flow orchestrates, sub-agent handles open-ended steps)
else:
    use sub-agent (start autonomous, add flows later for guardrails as needed)

If the approach is not obvious from context, ask the user whether they want more control over the conversation (flow-based) or a more autonomous experience (sub-agent). Frame it in terms of the trade-off: flows give predictability and auditability, sub-agents give flexibility and a more natural interaction. This is especially important when the user asks for multiple skills at once — each skill may warrant a different approach, so confirm the intent per skill before implementing.

Designing the skill boundary

Before implementing, outline:

1. Slots — the skill's interface. See rasa-managing-slots.
2. Flows — one per user goal. See rasa-building-flows.
3. Responses — See rasa-writing-responses.
4. Actions — backend operations. See rasa-writing-custom-actions.
5. Sub-agents — MCP servers and tools. See rasa-setting-up-react-agents or rasa-setting-up-a2a-agents.

File organization

A single-flow skill can live in one file (e.g. data/track_order.yml). When a skill contains multiple flows, group them in a subdirectory named after the skill:

data/
├── track_order.yml              # single-flow skill
├── booking/                     # multi-flow skill
│   ├── book_flight.yml
│   ├── select_destination.yml
│   └── choose_seats.yml
├── payments/
│   ├── process_payment.yml
│   └── verify_payment.yml
domain/
├── booking.yml
├── payments.yml
sub_agents/
├── policy_search/
│   └── config.yml

Related skills

Skill	Use for
rasa-building-flows	Writing flows, branching logic, call/link steps
rasa-managing-slots	Defining slots, types, mappings, persistence
rasa-writing-responses	Bot responses and utter_ask_* templates
rasa-writing-custom-actions	Custom actions and validation actions
rasa-setting-up-react-agents	ReAct sub-agents with MCP tools
rasa-setting-up-a2a-agents	External sub-agents via A2A protocol
rasa-calling-mcp-tools-from-flows	Invoking MCP tools directly from flow steps
rasa-configuring-mcp-server	MCP server setup in endpoints.yml
rasa-configuring-assistant	Pipeline, policies, config.yml / endpoints.yml
rasa-writing-e2e-tests	End-to-end conversation tests

Examples

For worked examples (flight booking, stock research, payments, insurance claims, Jira), see references/examples.md.