Feature Flag Implementation is an Optimizely Opal agent that generates a portable SKILL.md file to implement an Optimizely Feature Experimentation flag in a codebase.
- Challenge – Developers implement feature flags by hand and guess at flag keys, variable types, and version-specific SDK methods.
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Agent outcome – The agent produces a self-contained
SKILL.mdfile with the resolved flag entities, ordered implementation steps, copy-ready SDK snippets, guardrails, and a verification checklist. - Value – Coding assistants implement the flag correctly on the first attempt, shortening implementation time and preventing runtime failures from incorrect keys.
Required Optimizely products
The Feature Flag Implementation agent requires Feature Experimentation.
Install agent
Install the agent from the Opal Agent Directory.
- Go to Agents > Agent Directory.
- Select Feature Flag Implementation.
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Click Install Agent to add it to your Opal instance.
Use the agent
In Opal Chat, enter @feature_flag_implementation and provide the following details:
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Flag Name– The human-readable name of the flag, such as Free Shipping Hero. The agent searches for matching flags in the resolved project, displays the matches, and asks for confirmation before generating the skill. If the search returns multiple matches, the agent asks which flag to use. - (Optional)
Project Name– The human-readable name of the Feature Experimentation project, such as Web Store FX. Provide this value or the Project ID. If the name is partial or matches more than one project, the agent lists the matches and asks which project to use. - (Optional)
Project ID– The Feature Experimentation project ID as a string, such as 5362402791784448. This is optional when you provideProject Nameinstead. Pass the value as a string to avoid precision loss on large IDs. - (Optional)
SDK Language & Version (optional)– The SDK language and, when known, the version, such as React v4, Python 5.x, or Node.js v5. The agent treats this value as a starting hint. The generated skill re-verifies the installed version from the codebase dependency manifest.
The agent returns a canvas with a downloadable SKILL.md file. Coding assistants such as Claude, Cursor, and GitHub Copilot discover and load the file because it follows the Agent Skills convention. The file includes an entity reference, ordered implementation steps, copy-ready SDK snippets, guardrails, and a verification checklist.
To use the Feature Flag Implementation 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 Flag Implementation 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 Flag Implementation agent takes the following inputs:
Flag Name- (Optional)
Project Name - (Optional)
Project ID - (Optional)
SDK Language & Version (optional)
Tools
The Feature Flag Implementation agent uses the following tools to process your request:
exp_get_schemasexp_execute_queryexp_search_fx_sdk_docscreate_canvascode_executeedit_filewrite_filesearch_fileslist_filesread_file
Additional details
The agent uses the following default configuration:
- Inference level – Standard. Provides fast, efficient responses.
- Files – None.
- Output – Text. A portable, self-contained SKILL.md following the Agent Skills convention (YAML frontmatter with name + description, then a Markdown body). Any LLM coding assistant (Claude, Cursor, Copilot, etc.) can discover and load it to implement the FX flag in code — including entity reference, ordered implementation steps, copy-ready SDK snippets, guardrails, and a verification checklist.
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.
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