Feature Experimentation Governance agent

  • Updated

Feature Experimentation Governance is an Optimizely Opal agent that analyzes an Optimizely Feature Experimentation project and generates a read-only HTML governance report on a canvas.

  • Challenge – Feature flags accumulate across environments, and teams lose visibility into which flags are live, stale, or abandoned.
  • Agent outcome – The agent produces a client-ready HTML report with flag counts, a rule-type breakdown, health classification, hygiene indicators, priority review and cleanup lists, and tiered recommendations.
  • Value – Teams identify cleanup and promotion opportunities in one pass, which reduces technical debt and keeps flag inventory under control.

Required Optimizely products

The Feature Experimentation Governance agent requires Feature Experimentation.

Install agent

Opal administrators, agent builders, and Opal users with the Add, edit, and install specialized agents  attribute for a custom role can add agents to their organization's Optimizely Opal instance. See Add users and set permissions.

Install the agent from the Opal Agent Directory.

  1. Go to Agents > Agent Directory.
  2. Select Feature Experimentation Governance.

  3. Click Install Agent to add it to your Opal instance.

Use the agent

In Opal Chat, enter @feature_experimentation_governance and provide the following details:

  • Project Name – Full or partial name of the Feature Experimentation project to analyze. The agent supports partial matches, searches for the project, and confirms the match before it runs.

The agent returns a canvas with a self-contained, read-only HTML governance report. The report covers flag counts, a rule-type breakdown, health classification, lifecycle hygiene indicators, a priority review list of stale active flags, cleanup opportunities, and tiered recommendations.

To use the Feature Experimentation Governance agent in a workflow agent, drag and drop it into your workflow. See Create a workflow agent.

Details

These are the default details for the Feature Experimentation Governance agent. After you install the agent in your Opal instance, customize these details for your organization's needs. See Manage agents for instructions.

Input variables

The Feature Experimentation Governance agent takes the following input:

  • Project Name

Tools

The Feature Experimentation Governance agent uses the following tools to process your request:

  • exp_get_schemas
  • exp_execute_query
  • exp_summarize_test_result
  • code_execute
  • create_canvas

Additional details

The agent uses the following default configuration:

  • Inference level – Standard. Provides fast, efficient responses.
  • Files – None.
  • Output – Text. A client-ready, self-contained, read-only HTML Feature Governance & Health report with flag counts, rule-type (Kind) breakdown, deterministic health classification, hygiene indicators, Priority Review and Cleanup lists, tiered recommendations, and advisory recommended-action badges (no interactive controls).

If you use Opti ID, administrators can turn off generative AI in the Opti ID Admin Center. See Turn generative AI off across Optimizely applications.