In Coach, simulations work because Coach loads skills — guided recipes that handle the right multi-step sequence (set up a test customer, write strong assertions, choose the right execution environment, etc.) automatically based on your intent. You don’t think about skills; they just happen.
The MCP server is different. MCP exposes the underlying Lorikeet tools directly to your AI assistant — there’s no automatic orchestration. If you just say “create a sim for the refund flow”, the AI calls raw tools and often misses prerequisites: simulations created without test customer profiles, weak assertions, wrong execution environment, silent failures that look fine in the UI.
To get the same guided experience over MCP, you invoke the skill explicitly.
Coach: skills load automatically from intent.
MCP: skills must be invoked explicitly — syntax varies by client.
How to invoke a sim skill on MCP
Claude Code
Claude (desktop / web)
ChatGPT
Other MCP clients
Type the skill as a slash command at the start of your prompt:/lorikeet:create-simulations build simulations for the refund workflow
Ask Claude to load the skill explicitly, then describe your task:Load the Lorikeet create-simulations skill, then build sims for the refund workflow.
load_prompt tool to fetch the skill content, then proceeds. With the Lorikeet app enabled in your workspace:Use the Lorikeet load_prompt tool to load the "create-simulations" skill, then build sims for the refund workflow.
For Cursor, Continue, Cline, and other MCP clients, the universal pattern works:Use the Lorikeet load_prompt tool to load "create-simulations", then build sims for the refund workflow.
Skip the skill invocation and the AI improvises from raw tools. Most common consequences: simulations created without test customer profiles, weak or missing assertions, wrong execution environment, silent failures. Always invoke the skill first.
End-to-end example: creating and running sims via MCP
Here’s the canonical flow using Claude Code. Adjust the slash command syntax per the tabs above for other clients.
Create simulations for a workflow
/lorikeet:create-simulations create simulations for the refund workflow,
covering valid refunds, expired return windows, and missing orders.
- Analyze the workflow
- Set up a test customer profile if needed
- Generate scenarios with clear instructions and initial messages
- Define expected results and assertions
- Confirm with you before creating
Run the simulations
/lorikeet:run-simulations run the simulations I just created and report the results.
Iterate on failures
/lorikeet:simulation-driven-development iterate on the failing sims until pass rate is at least 90%.
Edit a scenario if needed
/lorikeet:update-simulations strengthen the assertions on the "expired return window" scenario.
Review your sim coverage
/lorikeet:review-simulations review the simulations for the refund workflow — what's missing?
Simulation skills reference
| Skill | When to use it |
|---|
create-simulations | Create new test scenarios and test customers for a workflow |
run-simulations | Execute existing simulations and review results |
update-simulations | Edit an existing scenario (instructions, assertions, expected results) |
review-simulations | Audit existing simulations for coverage, clarity, and quality |
simulation-driven-development | Iterate to push simulation pass rates higher (audit → baseline → fix → re-run) |
Other Lorikeet skills available via MCP
The same skill-invocation pattern works for non-simulation tasks. Replace create-simulations with the relevant skill name:
| Skill | Purpose |
|---|
edit-workflow | Safely edit a workflow on a draft version |
build-guardrail | Create or improve a guardrail |
diagnose-guardrails | Analyze guardrail performance and find gaps |
knowledge-creator | Add new knowledge to Lorikeet, routed to the right primitive |
knowledge-gaps | Find missing knowledge from escalated tickets |
understanding-tqs | Diagnose why TQS is failing |
improve-check-score | Diagnose and fix a failing TQS check |
diagnose-ticket | Investigate what happened on a specific ticket |
setup-integration | Configure a ticketing or external system integration |
design-campaign | Design and launch an outbound campaign |
Troubleshooting
Output looks incomplete or missing setup steps — you likely didn’t invoke a skill. Retry with the slash command or load_prompt instruction.
My MCP client doesn’t support slash commands — use the universal fallback: “Use the Lorikeet load_prompt tool to load <skill-name>, then…”.
I want to see what a skill does before invoking it — call load_prompt(<skill-name>) directly via MCP; the content returns inline.
Still stuck? Reach out to the Lorikeet team. 
