Before writing a prompt, get to know the user with the astria CLI (see the
astria-api skill):
astria prompts list --limit 20— their recent prompts, to learn their style and parameters.astria packs list— their packs. If the request is about a specific subject (e.g. a shirt), find a pack whosemain_class_namematches and inspect its template prompts withastria prompts list --pack-id <id>.astria tunes list— their references/tunes. If any match what they want to generate, reference it in the prompt via<model_type:id:1> namesyntax (see theastria-apiskill).
Do not send the user off to browse packs or tunes themselves — query with the
CLI and bring concrete suggestions back to them. When offering choices, the
AskUserQuestion tool with image thumbnails helps them pick.
If no tune matches the request, follow intent:
- For headshots / models / avatars, do NOT ask for a reference first. Propose ready-to-generate prompt options and trait options (look, age range, styling, framing, lighting), then confirm generation settings.
- For product or person-specific identity requests where likeness matters, ask the user to provide a reference image (upload it as a tune with
astria tunes create, or drag it into the prompt box in the web app). - Do not suggest web search for this flow.
After writing a prompt, show the user the prompt text and let them review or
edit it before generating. Confirm how many images per prompt (via
AskUserQuestion) before calling astria generate.
- E-commerce / product shots — reference tunes to create a new image.
- Image editing — pass
astria generate --input-image <url|file>to modify an existing image (change background, change style, add/remove objects). - Upscaling —
astria generate --model gemini --text "Recreate this image in 4K" --input-image <url>. If the image has prominent text labels, mention them in the prompt so they survive the upscale.
By default generate with the gemini model (astria generate --model gemini).
No need to ask the user about model type unless they explicitly mention another
one or ask for a recommendation.
Default intent mapping
If the user asks to create "models", "avatars", or "headshots", interpret this as a request for realistic, unique face headshots on a clean white studio background:
- Do not use any reference tune for this request type.
- Keep framing as a face headshot (not full body), white
#fffstudio backdrop, studio lighting. - Proactively offer prompt/trait choices with
AskUserQuestioninstead of asking for references. - Treat nationality words ("israeli", "french", "japanese") as styling/trait guidance for facial features and casting diversity, not as a request for references.
- Do NOT suggest fashion, lookbook, lifestyle, full-body, or outfit-led prompts for this request type unless the user explicitly asks for those.
See the unique-headshot skill for the detailed face-trait template.
Interaction rule (strict)
Never ask a question and suggest prompt text in the same response.
- If you use
AskUserQuestion, return only questions/options in that turn. - After the user answers, return the prompt suggestion(s) in the next turn.
References
For a reference tune always use <model_type:tune.id:1> tune.name to reference
the trained subject:
portrait of <faceid:123:1> woman in a garden wearing <faceid:124:1> dress— CORRECTportrait of John in a garden— WRONG (the model doesn't know "John")
Reviewing bad results
If the user says results are bad, figure out what went wrong:
- Inspect each reference's
orig_images(astria tunes get <id>) and check thenamematches the image content. Ifname=womanbut the image is a full-body shot including clothes or a hat, tell the user to re-crop the training images on that tune's page (/tunes/<id>→ "training images" → crop tool). - The
namemust represent the main subject. "jewelry" is a poor name — it should be "ring" or "necklace" depending on the subject. If a tune named "jewelry" holds a ring, suggest renaming it (astria tunes update <id> --name ring) and retraining.
Key parameters
| Parameter | CLI flag | Common values |
|---|---|---|
| Prompt text | --text |
Required |
| Number of images | --num-images |
1–4 |
| Aspect ratio | --aspect-ratio |
1:1 16:9 9:16 21:9 9:21 3:2 2:3 5:4 4:5 4:3 |
| Resolution (gemini only) | --resolution |
1K, 2K (default), 4K |
Tips for better results
- Include background descriptions: "clean white studio", "blurred urban street", "autumn forest".
- For product shots, describe the surface and arrangement.
- Always work with a consistent face reference. If the user has none, suggest a faceid tune from the public gallery (
astria tunes list --gallery --model-type faceid --limit 200) or generate a face first (no reference) and convert one of those outputs into a tune withastria tunes create. - Figure out the intent — a lookbook (e.g. prompt
look book plain white background #fff) or a campaign shot. Campaign example:A direct flash paparazzi style shot of <faceid:3904080:1.0> woman moving through a crowded bar. She looks straight into the lens with an intense expression. She wears the <faceid:3907553:1.0> dress and the <faceid:3907242:1.0> bag on her shoulder. The background is dark and out of focus. High contrast, sharp flash.