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Documentation Index

Fetch the complete documentation index at: https://docs.lorikeetcx.ai/llms.txt

Use this file to discover all available pages before exploring further.

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.

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How to invoke a sim skill on MCP

Type the skill as a slash command at the start of your prompt:
/lorikeet:create-simulations build simulations for the refund workflow
Claude Code will load the recipe and follow it end-to-end.
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.

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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.
1

Create simulations for a workflow

/lorikeet:create-simulations create simulations for the refund workflow,
covering valid refunds, expired return windows, and missing orders.
The skill will:
  • 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
2

Run the simulations

/lorikeet:run-simulations run the simulations I just created and report the results.
The skill will execute the batch, poll for completion, and present pass/fail with reasoning per scenario.
3

Iterate on failures

/lorikeet:simulation-driven-development iterate on the failing sims until pass rate is at least 90%.
The skill will classify each failure, propose targeted fixes, apply them on a draft, re-run, and repeat until the target is hit.
4

Edit a scenario if needed

/lorikeet:update-simulations strengthen the assertions on the "expired return window" scenario.
5

Review your sim coverage

/lorikeet:review-simulations review the simulations for the refund workflow — what's missing?
The skill grades expected-result reliability, instruction clarity, test customer completeness, and coverage.

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Simulation skills reference

SkillWhen to use it
create-simulationsCreate new test scenarios and test customers for a workflow
run-simulationsExecute existing simulations and review results
update-simulationsEdit an existing scenario (instructions, assertions, expected results)
review-simulationsAudit existing simulations for coverage, clarity, and quality
simulation-driven-developmentIterate to push simulation pass rates higher (audit → baseline → fix → re-run)

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Other Lorikeet skills available via MCP

The same skill-invocation pattern works for non-simulation tasks. Replace create-simulations with the relevant skill name:
SkillPurpose
edit-workflowSafely edit a workflow on a draft version
build-guardrailCreate or improve a guardrail
diagnose-guardrailsAnalyze guardrail performance and find gaps
knowledge-creatorAdd new knowledge to Lorikeet, routed to the right primitive
knowledge-gapsFind missing knowledge from escalated tickets
understanding-tqsDiagnose why TQS is failing
improve-check-scoreDiagnose and fix a failing TQS check
diagnose-ticketInvestigate what happened on a specific ticket
setup-integrationConfigure a ticketing or external system integration
design-campaignDesign and launch an outbound campaign

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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.