fal.ai Image

Use this skill when the user wants to generate or edit images through fal.ai, compare multiple marketplace image models, or build repeatable experiment workflows with prompts, references, outputs, and costs tracked in a consistent way.

Philosophy: Standardize The Harness, Not The Image Model

fal gives one platform surface for many image models, but the useful controls still differ by model family. The right abstraction is:

• standardize auth, queueing, file handling, output capture, and cost tracking
• keep model-specific knobs explicit
• compare models on the same task, not by pretending they all expose the same schema

Before generating, ask:

• Is this a fresh generation or an edit run?
• What must stay constant across models: prompt intent, reference images, size target, transparency, or output count?
• Which model-specific controls materially affect fairness and need to be frozen?
• Do we need pre-run cost estimates, per-run request IDs, or both?