Build an Employee Access Request and Lifecycle Agent
Build an agent that converts employee access requests and job changes into policy-checked provisioning plans. Collect approvals, apply changes to mock accounts, and show the resulting permissions with an audit trail.
What you are building
The core problem, expected build, and operating context for this challenge.
An IT team processing access requests and employee changes.
Build an agent that converts employee access requests and job changes into policy-checked provisioning plans. Collect approvals, apply changes to mock accounts, and show the resulting permissions with an audit trail.
Employee lifecycle events
Role-to-permission rules
Approval records and current accounts
Validate identity and the latest lifecycle state.
Compute required permission changes from the role policy.
Collect required approvals.
Apply approved changes in the mock identity store and verify the final state.
An access request queue with current and proposed permissions, approval controls, and verification logs.
Remove the sales permissions, grant tickets-read in the mock store, and show the verified before-and-after state.
A working local application with the specified review interface.
Source code, dependency lockfile, and setup commands.
A recorded end-to-end demo using the supplied starter data.
Example outputs, action logs, and automated tests.
These fictional records are a small development fixture, not a production dataset. Implement the mock services described in the brief.
```json { "employee": { "id": "E1", "event": "transfer", "new_role": "support" }, "current_permissions": [ "sales-read", "sales-write" ], "role_policy": { "support": [ "tickets-read" ] }, "approval": { "approved": true, "employee_id": "E1", "role": "support" } } ```
Use mock identities only. Do not connect real administrator credentials. Choose an available model that supports your implementation. Record its identifier and version.
Review the complete application, not only the starter-case answers.
The final permissions contain only tickets-read.
The approval matches the employee and requested role.
Repeated processing does not create extra grants. Add one normal case, one incomplete-input case, and one failure-recovery case.
Participation guide
Use mock identities only. Do not connect real administrator credentials.
How work is evaluated
Review workflow completion, interface usability, evidence quality, and safe failure handling. No agent execution has been verified.
A working local application with the specified review interface. Source code, dependency lockfile, and setup commands. A recorded end-to-end demo using the supplied starter data. Example outputs, action logs, and automated tests.
Challenge datasets
Public datasets, plus the private datasets you have access to.
What you should walk away with
Validate identity and the latest lifecycle state.
Compute required permission changes from the role policy.
Collect required approvals.
Apply approved changes in the mock identity store and verify the final state.
Reference links and supporting material
Supplied fictional starter records: Employee lifecycle events, Role-to-permission rules, Approval records and current accounts. The overview includes the complete JSON bundle. Implement local mock services and extend the sample coverage.
Challenge setup
Configuration summary for this challenge.
Challenge input
Input details are not configured.
LangGraph
Runtime for stateful agent workflows.
Evaluated output
No output checks are configured.
- No evaluation checks are configured.
- 1 public reference case
- 1 configured tool
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
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Configured tools
- LangGraph ยท Optional
Evaluation contract
- No evaluation checks are configured.
Reference cases
- 1 public reference case
Workflow tasks
No workflow tasks are configured.
Recipe freeze marker
No recipe freeze time is recorded.