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# Generation configs

> What a generation config contains, how it governs every run, and the rules configs follow including versioning and pinned output structure.

A generation config is the recipe for your enrichment runs. It captures everything the engine needs to know about your brand, your goals, and your rules — so you set it up once and every run after that starts from a proven baseline instead of a blank page.

## How your inputs become rules

Your inputs don't get handed to the generator as-is. **An agent reads them and writes the rules for the enrichment run — and it writes those rules at the field level.**

![Diagram: brand voice, keywords, and additional context flow into an agent, which writes per-field rule sets — for example product title, meta description, and conversational Q\&A — each with a description, requirements, and pinned structure constraints. A plain-English summary comes back for sanity-checking.](/_fern-files/feedonomics.docs.buildwithfern.com/dc3e079ed79bee823c34ef5e06bd077ca0e7c9569cf9b9cc6e2f7be9fd158ec0/docs/assets/enrichment/inputs-to-rules.svg)

That distinction matters. You describe your brand once, in one place. The agent takes your **brand voice instructions**, your **keywords**, and your **additional context**, and translates them into specific instructions for every individual field the run will produce — what a product title should do with your voice, what a meta description should do with your keywords, what a conversational Q\&A should emphasize.

For each field, the agent writes:

* **A description** of what that field should contain, with your brand and goals already baked in.
* **Requirements** — both hard rules (length limits, formats) and soft guidance (tone, emphasis).
* **Structure constraints** that pin the output to exactly the shape the field expects.

This is why a vague brand voice input produces flat results across the board: it isn't one prompt getting diluted, it's twenty field-level rule sets each getting a little less to work with.

You get back a plain-English summary of what the config will do, plus per-field reasoning, so you can sanity-check the rules before spending a run on them.

## The inputs you provide

### Brand voice

Your voice, tone, do's and don'ts, restricted claims, and vocabulary. This is the input that most affects your results, and it's worth real effort — see [Teaching enrichment your brand voice](/product/enrichment/brand-voice) for what to include.

> **Brand voice is limited to 10,000 characters**
>
> That's a generous amount of room — several pages of guidance — but it does mean a full brand book won't fit verbatim. If you're up against the limit, keep the parts that change how a sentence gets written (personality, tone by context, do's and don'ts, restricted claims, vocabulary) and drop the parts that don't (history, logo usage, color palettes, print specifications).

### Additional context

Anything the agent should know that isn't brand voice. **Use single-line instructions** — short, direct statements rather than prose.

Additional context is the right place for two things:

* **Instructions beyond the scope of your brand voice.** Guidance that isn't about how you sound, but about what this run should do. *"Prioritize durability and load capacity over aesthetics."* *"These are professional-grade tools, not consumer DIY."*
* **Specific concepts the agent should pay attention to.** A detail you know matters for this catalog that the agent wouldn't infer on its own. *"Sizing runs small — mention fit guidance where relevant."* *"Assembly is required on all items in this collection."*

Keep each instruction to one line and one idea. A list of five sharp single-line instructions steers generation far better than a paragraph, because each one lands cleanly in the field-level rules the agent writes.

> **Brand voice or additional context?**
>
> Ask whether it would still be true on a different set of products. If yes, it's brand voice — it belongs everywhere. If it's specific to this catalog, collection, or run, it's additional context.

### Keywords and purpose

Your target search terms and what you're optimizing for. Both are covered in [Inputs and what happens to them](/product/enrichment/inputs).

## The rules configs live by

**Configs are versioned, never edited.** When you want to change something, you create a new config rather than modifying the old one. This means every run is traceable to exactly the configuration that produced it, and a config that worked last month still works the same way today.

**Structure is never improvised.** The shape of each output field — its length limits, format, and schema — is fixed by the platform, not generated. The AI writes the words; it doesn't get to redesign the fields.

**Gaps get flagged, not papered over.** If your inputs are missing something critical, config creation stops and tells you what's needed. Minor gaps are advisory — you can proceed, with eyes open.

**Your raw inputs aren't kept.** Only the finished config and its summary are stored. The brand documents and keyword files you upload during setup are used to build the config, not retained afterward.

## Saved configs

Every config you create is saved and selectable from a dropdown at run time. Most teams end up with a small library — one per brand, or one per major product category — and reuse them for months.

Ready to build yours? Start with [Teaching enrichment your brand voice](/product/enrichment/brand-voice), then see [Inputs and what happens to them](/product/enrichment/inputs) for the full set of setup fields.