Arcads external API

Configuration

Base URL:

https://external-api.arcads.ai

(or

ARCADS_BASE_URL

Auth: HTTP Basic — use
```
ARCADS_API_KEY
```
as the username and an empty password unless Arcads documentation for your key specifies otherwise. Example curl:
```
curl -u "$ARCADS_API_KEY:" "$ARCADS_BASE_URL/v1/products"
```
.
Never print API keys, commit
```
.env
```
, or paste keys into
```
MASTER_CONTEXT.md
```
.

If the key is missing or the API returns 401/403

Editor-first (default): Ensure
```
.env
```
exists (copy from
```
.env.example
```
in the repo root). Ask the user to paste
```
ARCADS_API_KEY
```
only inside
```
.env
```
and save. Do not ask them to paste the key in chat unless they insist.
Chat-assisted: If they paste the key in chat, write
```
.env
```
for them, confirm "saved to
```
.env
```
" without repeating the key, and remind them that chat history may retain secrets—rotate the key in Arcads if the chat could be shared.

Before the first call, confirm

.gitignore

excludes

.env

Read order

Repo root MASTER_CONTEXT.md
when present (brand voice, decisions, quirks).
This skill's reference.md for routes, bodies, polling.
prompting/guide.md then the right prompting/prompt-library/
file for the model (see table below).

Decision tree: which flow?

All video models use

POST /v2/videos/generate

with the appropriate

model

value (see reference.md for the full

CreateVideoDto

schema).

User goal	Start here	Prompt library
Seedance 2.0 UGC video — selfie-style product review / testimonial	`POST /v2/videos/generate` with `model: "seedance-2.0"`	seedance-2.md (platform guide) + seedance-2-ugc.md (9-layer UGC formula)
Seedance 2.0 premium product reveal — dark-void, no person, text narrative	`POST /v2/videos/generate` with `model: "seedance-2.0"`	seedance-2.md + seedance-2-premium-reveal.md
Seedance 2.0 product hero — elemental effects, no person, splash/mist	`POST /v2/videos/generate` with `model: "seedance-2.0"`	seedance-2.md + seedance-2-product-hero.md
Seedance 2.0 studio lookbook — polished, voiceover, multi-look	`POST /v2/videos/generate` with `model: "seedance-2.0"`	seedance-2.md + seedance-2-studio-lookbook.md
Seedance 2.0 feature walkthrough — fast-paced feature demo	`POST /v2/videos/generate` with `model: "seedance-2.0"`	seedance-2.md + seedance-2-feature-walkthrough.md
Reverse-engineer a video style into a reusable Seedance 2.0 template	Follow the analyze-video skill	prompting/analyze-video/SKILL.md
Clone/replicate an existing video ad for a different product	Follow the clone-ad skill	prompting/clone-ad/SKILL.md
Raw Sora 2 video from text (plus product)	`POST /v2/videos/generate` with `model: "sora2"`	prompt-library/sora-2.md
Sora remix of an existing asset	`POST /v1/sora2/remix/video`	sora-2.md
Veo 3.1 video	`POST /v2/videos/generate` with `model: "veo31"`	prompt-library/veo-3-1.md
Kling 3.0 video	`POST /v2/videos/generate` with `model: "kling-3.0"`	kling-3.md
Grok Video	`POST /v2/videos/generate` with `model: "grok-video"`	See reference.md for fields
Nano Banana still image (standalone or as starting frame for video)	`POST /v2/images/generate` with `"model":"nano-banana-2"` by default; optional `"model":"nano-banana"` (Nano Banana Pro)	nano-banana.md
B-roll clip (product-level)	`POST /v1/b-roll`	kling-3.md or nano-banana.md for craft; see reference.md for Kling/Nano routing notes
Scene generation	`POST /v1/scene`	Same as b-roll row
Recreate an influencer from a reference photo	Two-step: (1) `POST /v2/images/generate` with `refImageAsBase64` to generate a still image via Nano Banana, get user approval; (2) upload approved still → `POST /v2/videos/generate` with `model: "veo31"` and `startFrame` for video. Never skip the approval step.	prompt-library/influencer-recreation.md
Product showcase — AI person holds/uses a product and talks about it	Two-step: (1) `POST /v2/images/generate` with product `refImageAsBase64` ; (2) user approves still; (3) start-frame → video via `POST /v2/videos/generate` .	prompt-library/product-showcase.md
UGC / selfie-style (authentic reels, cross-model)	Any video model via `POST /v2/videos/generate`	prompt-library/ugc-selfie-style.md — cross-model UGC guide. For Seedance 2.0 specifically, use seedance-2-ugc.md instead.
Create a new AI influencer from text (character sheet)	Two-pass: (1) hero portrait via `POST /v2/images/generate` , get approval; (2) 9 angles with hero as `referenceImages` . Save to `references/influencers/` .	prompt-library/character-sheet.md
UGC product selfie — AI influencer holding a product	Combine character hero + product photo + style references as `referenceImages` .	prompt-library/ugc-product-selfie.md
Pixar-style 3D animated ad — anthropomorphized cartoon ad with mascot beats	Multi-step: (1) Lock cast sheet; (2) ChatGPT Image 2 storyboard stills via `POST /v2/images/generate` with `model: "gpt-image-2"` (max 5 `referenceImages` ); (3) Seedance 2.0 image-to-video per beat via `POST /v2/videos/generate` with `model: "seedance-2.0"` and `startFrame` from each still; (4) ffmpeg-stitch + burn captions.	../../shared/skills/pixar-style-ad/prompting/guide.md → storyboard-gpt-image-2.md + animate-seedance-2.md
Claymation / Aardman-style ad — sculpted plasticine characters, narrator-driven 8-beat story arc, 60–115s	Multi-step: (1) Lock cast sheet (protagonist + supporting character + narrator voice); (2) ChatGPT Image 2 storyboard stills via `POST /v2/images/generate` with `model: "gpt-image-2"` (max 5 `referenceImages` ) — fallback to `model: "nano-banana"` (Pro) for close-ups if clay texture flattens; (3) Seedance 2.0 image-to-video per beat via `POST /v2/videos/generate` with `model: "seedance-2.0"` ; (4) ffmpeg-stitch (optional `fps=12,fps=24` for stop-motion judder) + burn captions.	../../shared/skills/claymation-ad/prompting/guide.md → storyboard-gpt-image-2.md + animate-seedance-2.md
Add captions to a finished video — burn timed narrator/dialogue captions onto an existing MP4 (any source — claymation, pixar, UGC, B-roll)	Out of band (no Arcads API call). Multi-step: (1) `npx hyperframes init <run-id>-captions` ; (2) `npx hyperframes transcribe source.mp4 --model medium.en` (NOT `small.en` if there's background music); (3) group word-level transcript into reading phrases; (4) write captions-only HTML over `#ff00ff` magenta bg — never include `<video>` or `<audio>` elements (causes black-bar bug); (5) `npm run render` then ffmpeg `chromakey=0xff00ff:0.10:0.05` overlay onto source.	../../shared/skills/caption-video/prompting/guide.md
Talking avatar / script (actors, voices)	`POST /v1/scripts` , `POST /v1/scripts/{id}/generate`	prompting/guide.md
OmniHuman	`POST /v1/omnihuman`	prompting/guide.md
Audio-driven	`POST /v1/audio-driven`	prompting/guide.md

Prefer the shortest path: if the user only needs a single model, do not create scripts unless they ask for actors/lip-sync workflows.

Creative layer

MANDATORY: Before composing any prompt for the API, read the relevant
prompting/prompt-library/*.md
file for the chosen model/workflow. Do NOT skip this step — every prompt must align with the vendor guide's formula and best practices.
Build one clear prompt paragraph; avoid keyword soup.
For Seedance 2.0 / Sora2 / Veo3.1 / Kling / Grok Video / Nano Banana, align with the official vendor guides linked in each
```
prompting/prompt-library/*.md
```
file (do not paste full vendor docs into chat—summarize checks).
Merge slot values from the user and from MASTER_CONTEXT.md
when it conflicts with defaults.

Session setup: auto-create a dated folder

At the start of each session that will generate assets, create a folder and project for the day so everything is organized in the Arcads dashboard:

Get today's date as
```
YYYY-MM-DD
```
.
```
GET /v1/products
```
→ pick the target product (default to whichever
```
MASTER_CONTEXT.md
```
specifies under "My workspace"). If no default is set: if only one product exists, auto-populate
```
MASTER_CONTEXT.md
```
with its ID and name; if multiple, ask the user to pick and save their choice to
```
MASTER_CONTEXT.md
```
.

Check existing folders (

GET /v1/products/{productId}/folders

) — if "Arcads API - {today}" already exists, reuse it. Otherwise:

POST /v1/folders

with

{"productId": "...", "name": "Arcads API - YYYY-MM-DD"}

POST /v1/projects

with

{"productId": "...", "folderId": "...", "name": "Arcads API - YYYY-MM-DD"}

Store the
```
projectId
```
for the session and pass it in every generation call (
```
projectId
```
field on Sora2/Veo31/b-roll/scene/image DTOs) and use
```
POST /v1/assets/add-to-project
```
after generation for asset types that do not accept
```
projectId
```
directly.

This ensures every generated asset is findable in the Arcads dashboard under Product → "Arcads API - {date}".

Credit cost estimation (MANDATORY — show before generating)

Before firing any generation calls, calculate and present the total credit cost to the user as an estimate. Do not generate until the user confirms.

ALWAYS label credit totals as estimates and tell the user to confirm the exact cost in the Arcads platform before generating if precision matters. The Arcads API does not expose billing endpoints; pricing varies by duration, resolution, and reference inputs.

Cost data sources (in priority order)

logs/arcads-api.jsonl
— historical record of actual
```
creditsCharged
```
values for every previous call. Read this first. Grep for entries with the same
```
model
```
and similar config (same
```
duration
```
,
```
resolution
```
,
```
referenceImagesCount
```
,
```
audioEnabled
```
) and use the recorded
```
creditsCharged
```
as the estimate. This is the most accurate source.
MASTER_CONTEXT.md
→ Credit costs — user-provided pricing rules (e.g. "Seedance 2.0 image-to-video ≈ 0.06/sec"). Use when no matching log entry exists.
Ask the user — if neither source has data for the config, ask the user and write the answer into
```
MASTER_CONTEXT.md
```
.

Never invent numbers. Always cite the source of the estimate ("based on log entry from YYYY-MM-DD" or "from MASTER_CONTEXT.md rate table").

How to calculate

total_credits ≈ sum(credits_per_model × variations_requested) for each model

Example output to user

Estimated credit cost:
  Seedance 2.0 (15s i2v) × 1 = ~0.9 credits   (from logs/arcads-api.jsonl 2026-04-09)
  Veo 3.1                × 2 = ~8 credits     (from MASTER_CONTEXT.md)
  ─────────────────────────────
  Estimated total: ~8.9 credits

⚠️ Estimate only — confirm exact cost in the Arcads platform before proceeding.
Proceed? (yes/no)

Always wait for confirmation before firing. If the user has a credit balance visible in

MASTER_CONTEXT.md

, warn them if the total would exceed it. If neither the logs nor

MASTER_CONTEXT.md

have data for the config, ask the user before the first generation and save the answer.

Exception — QA-fix retries (still images only): After the user has confirmed the initial batch, automatic regeneration to fix visible defects (see Generated image QA below) does not require asking again for credit confirmation. Each retry is still billed — note the extra

creditsCharged

when summarizing the session.

Generation count: multiple variations per prompt

Before firing any generation call, ask the user how many variations they want for this prompt. Default is 1 if they don't specify.

When the count is greater than 1, send N separate API calls with the identical payload. Do NOT batch them into a single request — the API has no batch parameter. Fire them in parallel where possible, then poll all asset IDs concurrently.

Present results as a numbered list so the user can compare and pick favorites.

Nano Banana image: model choice (

nano-banana-2

vs Nano Banana Pro)

For

POST /V2/images/generate

when using a Nano Banana engine:

Default:
```
"model": "nano-banana-2"
```
(Nano Banana 2).
Optional:
```
"model": "nano-banana"
```
when the user asks for Nano Banana Pro (the API has no
```
nano-banana-pro
```
enum — Pro maps to
```
nano-banana
```
; see nano-banana.md).

Before the first Nano Banana image call in a workflow, ask: "Use default Nano Banana 2, or Nano Banana Pro?" If they have no preference, use

nano-banana-2

. Include the chosen

model

in the credit estimate (separate rows in

MASTER_CONTEXT.md

if pricing differs).

Script and dialogue

For any video that features a person speaking, ask the user for the script (the exact words the AI person should say). This is separate from the visual prompt — it's the dialogue.

MANDATORY — dialogue confirmation gate

Before generating any video that contains spoken dialogue, the agent MUST:

Extract the dialogue lines from the full prompt and show them to the user in a dedicated block, separate from the visual/cinematography description.
Present them as a clean, numbered list with beat labels (hook / show / demo / verdict, or similar) and any silent beats clearly marked as
```
(silent beat — no dialogue)
```
.
Read the dialogue out loud in your head at a natural pace, time it against the target duration, and flag the total spoken word count plus whether it comfortably fits.
Explicitly ask for dialogue approval before moving on — e.g. "Approve this dialogue? (yes / edit / rewrite)". Never assume approval from earlier confirmations (tone, template, credit cost). Dialogue approval is its own gate.
Only after the user types
```
yes
```
(or equivalent) may you proceed to the credit cost confirmation and then generation. If the user says "edit" or proposes changes, revise and re-present the numbered dialogue block until they approve.

Presentation format (use this exact structure):

📝 Dialogue script (please confirm before I generate)

  1. [HOOK]   "Bro. BRO. Look what just showed up."
  2. [SHOW]   "The PAID SOCIAL stripe? Insane. Like, who greenlit this?"
  3. [DEMO]   (silent beat — thumb brushing the suede, small nod)
  4. [VERDICT] "I'm literally wearing these to the gym tomorrow. You guys have to see these in person."

Total spoken words: ~28  |  Target duration: 15s  |  Fits at natural pace: ✅

Approve this dialogue? (yes / edit / rewrite)

This gate applies to Seedance 2.0, Veo 3.1, Sora 2, and Scene — any flow where the model speaks. Skip for silent flows (B-roll, pure product-hero, premium-reveal with no voiceover, Nano Banana images).

Model-specific notes

For Seedance 2.0, Veo 3.1, and Sora 2: embed the dialogue in the
```
prompt
```
field using a
```
Dialogue: "..."
```
or
```
She speaks: "..."
```
pattern (these models generate speech from the text prompt).
For Seedance 2.0 specifically: before generating, always ask the user whether to enable audio output (
```
audioEnabled: true
```
). Also ask whether they want to supply
```
referenceAudios
```
(e.g. background music or a specific voice clip). Upload audio files via presigned URL if provided.
For Scene (
```
CreateSceneDto
```
): use the dedicated
```
script
```
field for dialogue and
```
prompt
```
for visuals.
For B-roll: no speech — b-roll is silent/ambient by nature. If the user wants speech, redirect to Seedance 2.0, Veo 3.1, Sora 2, or Scene.
For Nano Banana images: no speech — these are still images. Speech is handled in the subsequent video generation step.

Script length → video duration (auto-select)

Use the script's word count to automatically pick the best

duration

value. Average speaking pace: ~2.5 words per second (~150 WPM). Round up to the next available duration to give breathing room.

Sora 2 — duration enum:

[4, 8, 12, 16, 20]

seconds

Script length	Duration
1–8 words	4s
9–18 words	8s
19–28 words	12s
29–38 words	16s
39–48 words	20s
49+ words	Too long — offer to split (see below)

Veo 3.1 — no

duration

field

Veo 3.1 auto-determines video length (~8s typical). If the script exceeds ~20 words, warn the user that Veo may truncate dialogue and offer to split or switch to Sora 2 which has longer duration options.

Seedance 2.0 — duration: 4–15 seconds (continuous)

Seedance 2.0 supports any integer from 4 to 15. Use ~2.5 words/second, round up to the nearest second.

Script length	Duration
1–8 words	4–5s
9–15 words	6–8s
16–25 words	9–12s
26–35 words	13–15s
36+ words	Too long — offer to split into multiple clips

For no-dialogue styles (product hero, premium reveal), default to 15s.

Resolution: Default to

720p

. Only use

480p

if the user asks for a faster/cheaper test generation.

Aspect ratio:

9:16

(vertical, default for UGC/social) or

16:9

(landscape). No

1:1

support.

B-roll (Kling 3.0) — duration enum:

[5, 10]

seconds

B-roll is typically wordless. If the user insists on a timed clip with context:

Script length	Duration
1–12 words	5s
13–24 words	10s
25+ words	Too long — redirect to Sora 2 / Veo 3.1 for speech

Scene — no

duration

field

Scene auto-determines length. Use the

script

field for dialogue.

Splitting long scripts into multiple videos

If the script exceeds the maximum duration for the chosen model:

Tell the user the script is too long for a single video and show the word/duration math.
Offer two options:
- Split into segments — the agent breaks the script at natural sentence boundaries into chunks that each fit within the model's max duration. Each chunk becomes a separate generation call.
- Switch models — if they're on Kling (10s max), suggest Sora 2 (up to 20s).
If the user chooses to split, generate each segment as a separate video (respecting the generation count — if they asked for 3 variations, generate 3 of each segment).
Offer to stitch the final segments together using
```
ffmpeg
```
:
- Download all segment videos locally.
- Concatenate using
```
ffmpeg -f concat -safe 0 -i list.txt -c copy output.mp4
```
  (re-encode if codecs differ).
- Present the stitched file alongside the individual segments so the user has both.

Veo 3.1:

startFrame

referenceImages

— pick one

Veo 3.1 has two mutually exclusive image input modes. Never use both on the same call.

Mode	Field	When to use
Start frame	`startFrame` (presigned upload `filePath` )	User provides a reference image of a person or scene they want the video to start from. The video will animate from this exact image. Use this for influencer recreation, character consistency, or any "make this image come alive" request.
Reference images	`referenceImages` (array of `filePath` strings)	User provides images for style, mood, or visual tone — not to appear literally in frame. The model uses them as inspiration, not as a first frame.

Default rule: When the user provides a single reference photo of a person, always use
startFrame
unless they explicitly say they want it as a style reference.

Image handling: auto-upscale small inputs

Before sending any reference image, start frame, or base64 image to the API:

Check dimensions. If the image's longest side is below 1024 px, upscale it using Lanczos resampling so the longest side reaches 1080 px (preserve aspect ratio).
Convert to RGB JPEG (quality 90–95) to strip alpha channels and keep payload size reasonable.
Re-encode as base64 (for
```
refImageAsBase64
```
) or upload the resized file (for
```
startFrame
```
via presigned URL).

Several Arcads endpoints (notably

POST /v1/b-roll

) reject images below a minimum resolution with

422 — The provided image is too small

. Auto-upscaling prevents this silently so the user never hits the error.

Generated image QA (mandatory)

Applies to still images from Arcads, especially

POST /V2/images/generate

(Nano Banana and other image models). After each image asset reaches

status: generated

, visually inspect the output (download or open the image URL / use the agent's image-reading capability).

Look for: extra or missing hands or fingers; wrong limb count; distorted, duplicated, or merged facial features; melted or fused objects; impossible anatomy; stray limbs; obvious texture or boundary artifacts; unreadable or garbled text if text was requested.

If something looks wrong: Do not hand off the bad frame as the final deliverable without trying again. Regenerate with a revised prompt that explicitly corrects the issue (e.g. "exactly two hands, five fingers each, anatomically correct arms," "single face, no duplicate features"). Do not resend the identical payload and expect a different outcome.

Retry cap: Up to 2 regeneration attempts per originally requested image (3 attempts total including the first). If defects remain after the cap, stop auto-retries, tell the user what still looks wrong, show the best attempt or URLs for all attempts, and ask how they want to proceed.

Credits: Each attempt is a separate generation and is billed. Summarize total credits used for that image after the QA loop ends. See Exception — QA-fix retries under Credit cost estimation.

Video (optional quick check): Before spending heavily on downstream video, you may spot-check scene/b-roll thumbnails or extracted frames for the same kinds of defects; scope is lighter than for hero stills.

Details and checklist items: prompting/prompt-library/nano-banana.md.

Execution checklist (agent)

Session folder: Ensure today's dated folder + project exist (see above).
Resolve
```
productId
```
(and
```
projectId
```
from session folder):
```
GET /v1/products
```
or ask the user.
Ask for script/dialogue: If the output is a video with a person speaking, ask the user for the exact words. Count words to auto-select duration (see "Script length → video duration" above). If too long, offer to split. (Skip for Nano Banana image-only requests.)
- MANDATORY dialogue confirmation gate (before credit cost / before generation): Extract the dialogue lines from the drafted prompt and present them to the user as a dedicated, numbered block separate from the visual description. Follow the format in Script and dialogue → MANDATORY dialogue confirmation gate. Wait for explicit
```
yes
```
  before moving on. This gate is separate from the credit cost confirmation — both must be satisfied.
Nano Banana image model: For
```
POST /V2/images/generate
```
, confirm Nano Banana 2 (default) vs Nano Banana Pro (
```
nano-banana
```
) per the section above. Skip if not an image call.
Ask for generation count: Ask how many variations the user wants for this prompt. Default to 1.
Show credit cost and get confirmation: Calculate total credits using the cost table above. Present the breakdown to the user. Do NOT proceed until they confirm.
Check
references/
folder: Before composing the prompt, check the repo-root
```
references/
```
folder for relevant images:
```
references/influencers/
```
for person recreation,
```
references/products/
```
for product showcase,
```
references/aesthetics/
```
for style/mood. If the user hasn't provided an image but a relevant one exists in
```
references/
```
, offer to use it. Auto-upscale any reference image if needed. For Veo 3.1, determine whether to use
```
startFrame
```
or
```
referenceImages
```
(see section above — default to
```
startFrame
```
for person photos).
Compose JSON per OpenAPI / reference.md. Primary video endpoint:
```
POST /v2/videos/generate
```
with the appropriate
```
model
```
value (see
```
CreateVideoDto
```
in reference.md). Include
```
projectId
```
when the DTO supports it. Set
```
duration
```
based on script length for models that require it. For Nano Banana images, use
```
POST /v2/images/generate
```
with
```
model
```
set per the Nano Banana section (
```
nano-banana-2
```
unless the user chose Pro).
- Seedance 2.0 extras: Set
```
resolution
```
  to
```
720p
```
  (default). Set
```
aspectRatio
```
  to
```
9:16
```
  (UGC/social) or
```
16:9
```
  (landscape). Include
```
audioEnabled
```
  per user confirmation. If the user provided reference images, upload via presigned URL and pass
```
filePath
```
  strings in
```
referenceImages
```
  (max 3). Same for
```
referenceVideos
```
  and
```
referenceAudios
```
  if provided. Keep
```
@(img1)
```
  tokens in the prompt text alongside the
```
referenceImages
```
  array.
- ⚠️ Seedance 2.0 mutually exclusive input modes (confirmed 2026-04-09):
```
referenceVideos
```
  and
```
referenceImages
```
  cannot be combined in the same request — the API returns
```
HTTP 500 UNKNOWN_ERROR
```
  . Pick one: image-to-video OR video-to-video.
```
referenceAudios
```
  may be combined with either. See
```
reference.md
```
  for details.
- ~~Seedance 2.0 v2v + human faces~~ — RESOLVED 2026-04-14: v2v with people/faces in reference videos now works. Previously blocked by content checker (April 9). See
```
reference.md
```
  .
- ~~Seedance 2.0 audio+image 500 regression~~ — RESOLVED 2026-04-14:
```
audioEnabled: true
```
  +
```
referenceImages
```
  now works. Previously returned HTTP 500 (April 9). Always use freshly obtained presigned URLs. See
```
reference.md
```
  .
```
POST
```
the correct endpoint N times (once per requested variation) with the same payload. Fire in parallel where possible. Immediately after the POST succeeds, append a log entry to
logs/arcads-api.jsonl
with the request config (model, duration, resolution, aspectRatio, audioEnabled, reference counts, promptWordCount, assetId). Do NOT log the full prompt text, API keys, or Authorization headers.
Poll:
```
GET /v1/videos/{videoId}
```
for video IDs;
```
GET /v1/assets/{id}
```
for asset IDs (including Nano Banana images) until
```
status
```
is
```
generated
```
or
```
failed
```
(see reference.md). Poll all asset IDs concurrently. When polling completes, update the log entry with
```
response.status
```
,
```
response.creditsCharged
```
,
```
response.generationTimeSec
```
,
```
response.videoUrl
```
,
```
response.thumbnailUrl
```
, and
```
response.error
```
(if failed). See
```
logs/README.md
```
for the schema.
Generated image QA: For each still image produced in this turn (e.g.
```
POST /V2/images/generate
```
), follow Generated image QA: inspect the image; if defective, regenerate with a refined prompt until pass or 2 retries are exhausted. Skip this step for video-only outputs with no still to review.
Assign ALL assets to session project: After generation (and QA retries), check each asset's
```
projects
```
array. If it does not include the session
```
projectId
```
, call
```
POST /v1/assets/add-to-project
```
. This applies to every generated asset — including failed QA attempts and intermediate assets like Nano Banana stills used as starting frames for subsequent video generations. All assets from the session must end up in the same dated project folder.
Present results: Return watch URLs, image URLs, or download URLs for QA-passed stills (or the best attempt after max retries, with a clear note). If multiple variations, present as a numbered list for comparison. Explain
```
failed
```
with moderation/validation hints if
```
422
```
occurred. For Nano Banana images used as starting frames, show the image and wait for user approval before proceeding to video generation.

ALWAYS open the output folder on the user's machine after saving generated files so they can immediately review:
```
open "<output_directory>"
```
(macOS). Save videos to
```
outputs/
```
with a descriptive subfolder (e.g.
```
outputs/seedance-tests/
```
,
```
outputs/clone-ad-tests/
```
).

Stitch if split: If the script was split into segments, offer to stitch the final videos together with
```
ffmpeg
```
and provide both the stitched file and individual segments.

Errors (user-facing)

401/403: Fix API key / workspace access (setup flow above).
404: Wrong UUID; re-fetch lists.
422: Validation or moderation — tighten prompt, remove disallowed content, check required enums (aspect ratio, duration).
500: Retry later; if repeated, stop and report.

Supporting files

reference.md — endpoints, auth detail, polling, model mapping notes,
```
CreateVideoDto
```
schema.
prompting/guide.md — marketing brief → API.
Seedance 2.0:
- prompting/prompt-library/seedance-2.md — main Seedance 2.0 model guide (platform rules, API parameters, style template directory).
- prompting/prompt-library/seedance-2-ugc.md — 9-layer UGC selfie-style formula for Seedance 2.0.
- prompting/prompt-library/seedance-2-premium-reveal.md — dark-void premium product reveal (no person).
- prompting/prompt-library/seedance-2-product-hero.md — elemental product hero with splash/effects (no person).
- prompting/prompt-library/seedance-2-studio-lookbook.md — studio lookbook with voiceover.
- prompting/prompt-library/seedance-2-feature-walkthrough.md — fast-paced feature walkthrough demo.
- prompting/analyze-video/SKILL.md — reverse-engineer a reference video into a reusable Seedance 2.0 prompting template.
- prompting/clone-ad/SKILL.md — clone a reference video ad for a different product (end-to-end: analyze → adapt → generate).
Other models:
- prompting/prompt-library/influencer-recreation.md — analyze a reference photo and recreate the influencer.
- prompting/prompt-library/ugc-selfie-style.md — cross-model UGC guide (iPhone aesthetic, negative prompts, per-model formulas).
- prompting/prompt-library/product-showcase.md — product-in-hand video workflow (Nano Banana image → approve → video).
- prompting/prompt-library/nano-banana.md — Nano Banana image prompting guide.
- prompting/prompt-library/character-sheet.md — generate a 10-image character sheet for a new AI influencer from a text description.
- prompting/prompt-library/ugc-product-selfie.md — UGC selfie-style still image: character + product + style references.
prompting/brand-voice-starter.md — template to copy into
```
MASTER_CONTEXT.md
```
.

arcads-external-api

NPX Install

Tags

SKILL.md Content

Arcads external API

Configuration

If the key is missing or the API returns 401/403

Read order

Decision tree: which flow?

Creative layer

Session setup: auto-create a dated folder

Credit cost estimation (MANDATORY — show before generating)

Cost data sources (in priority order)

How to calculate

Example output to user

Generation count: multiple variations per prompt

Nano Banana image: model choice (
`nano-banana-2`
vs Nano Banana Pro)

Script and dialogue

MANDATORY — dialogue confirmation gate

Model-specific notes

Script length → video duration (auto-select)

Sora 2 — duration enum:
`[4, 8, 12, 16, 20]`
seconds

Veo 3.1 — no
`duration`
field

Seedance 2.0 — duration: 4–15 seconds (continuous)

B-roll (Kling 3.0) — duration enum:
`[5, 10]`
seconds

Scene — no
`duration`
field

Splitting long scripts into multiple videos

Veo 3.1:
`startFrame`
vs
`referenceImages`
— pick one

Image handling: auto-upscale small inputs

Generated image QA (mandatory)

Execution checklist (agent)

Errors (user-facing)

Supporting files

arcads-external-api

NPX Install

Tags

SKILL.md Content

Arcads external API

Configuration

If the key is missing or the API returns 401/403

Read order

Decision tree: which flow?

Creative layer

Session setup: auto-create a dated folder

Credit cost estimation (MANDATORY — show before generating)

Cost data sources (in priority order)

How to calculate

Example output to user

Generation count: multiple variations per prompt

Nano Banana image: model choice (nano-banana-2 vs Nano Banana Pro)

Script and dialogue

MANDATORY — dialogue confirmation gate

Model-specific notes

Script length → video duration (auto-select)

Sora 2 — duration enum: [4, 8, 12, 16, 20] seconds

Veo 3.1 — no duration field

Seedance 2.0 — duration: 4–15 seconds (continuous)

B-roll (Kling 3.0) — duration enum: [5, 10] seconds

Scene — no duration field

Splitting long scripts into multiple videos

Veo 3.1: startFrame vs referenceImages — pick one

Image handling: auto-upscale small inputs

Generated image QA (mandatory)

Execution checklist (agent)

Errors (user-facing)

Supporting files

Nano Banana image: model choice (
`nano-banana-2`
vs Nano Banana Pro)

Sora 2 — duration enum:
`[4, 8, 12, 16, 20]`
seconds

Veo 3.1 — no
`duration`
field

B-roll (Kling 3.0) — duration enum:
`[5, 10]`
seconds

Scene — no
`duration`
field

Veo 3.1:
`startFrame`
vs
`referenceImages`
— pick one