Driving Video Model Router from code

Everything the web app does is available over HTTP. The base URL is https://api.skillsafe.ai/v1/app-api, every request carries Authorization: Bearer <token>, and every response is the same envelope.

The `task` field comes first

This app has five lanes behind one endpoint. Every run body must carry a task field naming the lane - it is what the system prompt routes on. Send the wrong one and you get a valid package of the wrong kind; omit it and the model picks the closest lane and tells you which it chose.

One more shape trap: the run body is the input object. Do not wrap it in an {"input": ...} envelope - that returns 200 while hiding task from the model, which is the most confusing way this API can fail.

task Lane Fields Sections returned

pick Model selection shot, seconds, aspect, resolution, ref_images, needs_audio, needs_dialogue, needs_face, needs_motion, keyframes, needs_extend, needs_audio_upload Summary, Shortlist, Ruled Out, Recommendation, Trade-offs, Next Step

veo Veo 3.2 prompt shot, assets, seconds, aspect, resolution, style, audio, dialogue Summary, Atomic Elements, Reference Plan, Prompt, Config, Audio Direction, Next Step

port Cross-model port prompt, from_model, to_model, seconds, aspect, ref_images Summary, Capability Diff, Ported Prompt, What Changed, What Is Lost, Next Step

i2v Image to video image_desc, motion, end_frame, seconds, aspect, model, style Summary, Frame Plan, Motion Prompt, Config, Drift Risks, Next Step

v2v Video to video clip_desc, operation, change, seconds, model, style Summary, Operation Plan, Continuation Prompt, Handoff Frame, Pitfalls, Next Step

task	Lane	Fields	Sections returned
`pick`	Model selection	`shot, seconds, aspect, resolution, ref_images, needs_audio, needs_dialogue, needs_face, needs_motion, keyframes, needs_extend, needs_audio_upload`	Summary, Shortlist, Ruled Out, Recommendation, Trade-offs, Next Step
`veo`	Veo 3.2 prompt	`shot, assets, seconds, aspect, resolution, style, audio, dialogue`	Summary, Atomic Elements, Reference Plan, Prompt, Config, Audio Direction, Next Step
`port`	Cross-model port	`prompt, from_model, to_model, seconds, aspect, ref_images`	Summary, Capability Diff, Ported Prompt, What Changed, What Is Lost, Next Step
`i2v`	Image to video	`image_desc, motion, end_frame, seconds, aspect, model, style`	Summary, Frame Plan, Motion Prompt, Config, Drift Risks, Next Step
`v2v`	Video to video	`clip_desc, operation, change, seconds, model, style`	Summary, Operation Plan, Continuation Prompt, Handoff Frame, Pitfalls, Next Step

Only task, seconds and the lane's own required field are mandatory: shot for pick and veo, prompt and to_model for port, image_desc and motion for i2v, clip_desc, operation and change for v2v. Everything else has a sensible default. seconds and ref_images are numbers, not strings - sending "12" where 12 is expected is the most common 400. The needs_* fields are the strings "yes" or "no", and keyframes is one of none, start, end, both.

Add $model to any body to choose the model for that run: gpt-5.6-luna, gpt-5.6-terra (the default) or gpt-5.6-sol. Luna caps output at 4,096 tokens and will fail the pick, veo and port lanes rather than shorten them.

The response envelope

Success and failure have the same outer shape, so one check covers both.

{
  "ok": true,
  "data": {
    "...": "the result"
  }
}

{
  "ok": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "seconds should be number, got string",
    "details": {}
  }
}

HTTP error.code What it means

400 VALIDATION_ERROR The body was not a JSON object, or a declared field had the wrong type. A number field sent as a string is the usual cause.

401 UNAUTHORIZED No token, or a token that has expired or been revoked. Mint a new one.

402 INSUFFICIENT_CREDITS The balance is below the run's minimum. Call /estimate first and compare hold_credits against /me.

404 NOT_FOUND Wrong path, or a job id that does not belong to this token.

409 CONFLICT An Idempotency-Key replay whose body differs from the original request.

429 RATE_LIMITED Too many requests. Back off; do not tight-loop.

503 UPSTREAM_UNAVAILABLE The model provider is unavailable. Retry with backoff.

HTTP	error.code	What it means
`400`	`VALIDATION_ERROR`	The body was not a JSON object, or a declared field had the wrong type. A number field sent as a string is the usual cause.
`401`	`UNAUTHORIZED`	No token, or a token that has expired or been revoked. Mint a new one.
`402`	`INSUFFICIENT_CREDITS`	The balance is below the run's minimum. Call /estimate first and compare hold_credits against /me.
`404`	`NOT_FOUND`	Wrong path, or a job id that does not belong to this token.
`409`	`CONFLICT`	An Idempotency-Key replay whose body differs from the original request.
`429`	`RATE_LIMITED`	Too many requests. Back off; do not tight-loop.
`503`	`UPSTREAM_UNAVAILABLE`	The model provider is unavailable. Retry with backoff.

1. Get a token

Open /tokens.html in a browser and copy the token this app already holds - no developer console needed. A guest token is minted automatically and is enough for /me and /estimate; writing a package is metered and needs a personal token, which comes from signing in on that page.

Keep it in an environment variable rather than in source:

export SKILLSAFE_TOKEN="YOUR_TOKEN"

2. Check the session and the balance

GET /me is free. It returns only three fields: subject_type, subject_id and credits. Signed-in means subject_type == "user" - there is no username or email to test.

curl -sS -X GET "https://api.skillsafe.ai/v1/app-api/me" \
  -H "Authorization: Bearer $SKILLSAFE_TOKEN"

import json, urllib.request

TOKEN = "YOUR_TOKEN"   # from /tokens.html
BASE  = "https://api.skillsafe.ai/v1/app-api"

def call(method, path, payload=None, headers=None):
    data = json.dumps(payload).encode() if payload is not None else None
    req = urllib.request.Request(BASE + path, data=data, method=method)
    req.add_header("Authorization", "Bearer " + TOKEN)
    req.add_header("Content-Type", "application/json")
    req.add_header("Accept", "application/json")
    # A plain urllib request with no User-Agent is refused with 403.
    req.add_header("User-Agent", "video-model-router-client/1.0")
    for k, v in (headers or {}).items():
        req.add_header(k, v)
    with urllib.request.urlopen(req) as r:
        return json.loads(r.read())

out = call("GET", "/me")
print(json.dumps(out["data"], indent=2))

const TOKEN = "YOUR_TOKEN";   // from /tokens.html
const BASE  = "https://api.skillsafe.ai/v1/app-api";

async function call(method, path, payload) {
  const res = await fetch(BASE + path, {
    method,
    headers: {
      "Authorization": `Bearer ${TOKEN}`,
      "Content-Type": "application/json"
    },
    body: payload === undefined ? undefined : JSON.stringify(payload)
  });
  const json = await res.json();
  if (!res.ok || !json.ok) throw new Error(json.error?.message || res.statusText);
  return json.data;
}

const data = await call("GET", "/me");
console.log(data);

package main

import (
	"bytes"
	"fmt"
	"io"
	"net/http"
)

const base = "https://api.skillsafe.ai/v1/app-api"
const token = "YOUR_TOKEN" // from /tokens.html

func main() {
	req, _ := http.NewRequest("GET", base+"/me", nil)
	req.Header.Set("Authorization", "Bearer "+token)
	req.Header.Set("Content-Type", "application/json")
	res, err := http.DefaultClient.Do(req)
	if err != nil {
		panic(err)
	}
	defer res.Body.Close()
	out, _ := io.ReadAll(res.Body)
	fmt.Println(string(out))
}

import java.net.URI;
import java.net.http.*;

public class Main {
    static final String BASE  = "https://api.skillsafe.ai/v1/app-api";
    static final String TOKEN = "YOUR_TOKEN"; // from /tokens.html

    public static void main(String[] args) throws Exception {
        HttpRequest req = HttpRequest.newBuilder()
            .uri(URI.create(BASE + "/me"))
            .header("Authorization", "Bearer " + TOKEN)
            .header("Content-Type", "application/json")
            .method("GET", HttpRequest.BodyPublishers.noBody())
            .build();
        HttpResponse<String> res = HttpClient.newHttpClient()
            .send(req, HttpResponse.BodyHandlers.ofString());
        System.out.println(res.body());
    }
}

require 'net/http'
require 'json'
require 'uri'

BASE  = "https://api.skillsafe.ai/v1/app-api"
TOKEN = "YOUR_TOKEN" # from /tokens.html

uri = URI("#{BASE}/me")
req = Net::HTTP::Get.new(uri)
req["Authorization"] = "Bearer #{TOKEN}"
req["Content-Type"] = "application/json"
res = Net::HTTP.start(uri.hostname, uri.port, use_ssl: true) { |h| h.request(req) }
puts JSON.pretty_generate(JSON.parse(res.body)["data"])

<?php
$base  = "https://api.skillsafe.ai/v1/app-api";
$token = "YOUR_TOKEN"; // from /tokens.html

$opts = ["http" => [
    "method"  => "GET",
    "header"  => "Authorization: Bearer $token\r\nContent-Type: application/json\r\n",
]];
$res  = file_get_contents($base . "/me", false, stream_context_create($opts));
$json = json_decode($res, true);
print_r($json["data"]);

using System.Net.Http;
using System.Text;

const string Base  = "https://api.skillsafe.ai/v1/app-api";
const string Token = "YOUR_TOKEN"; // from /tokens.html

var http = new HttpClient();
http.DefaultRequestHeaders.Add("Authorization", $"Bearer {Token}");

var res = await http.SendAsync(new HttpRequestMessage(new HttpMethod("GET"), Base + "/me")
{
    Content = null
});
Console.WriteLine(await res.Content.ReadAsStringAsync());

3. Price the run before making it

POST /estimate costs nothing, creates no job, and returns the worst-case cost. Compare hold_credits against the balance from step 2 before you submit: a 402 after the fact is avoidable. hold_credits is a reservation priced at the full output cap - the actual charge is usually far lower.

It also echoes model, model_alias and markup_bps, which is the authoritative check that a run is bound to the model you think it is. Estimate each lane separately: their prompts and caps differ, so their holds do.

curl -sS -X POST "https://api.skillsafe.ai/v1/app-api/estimate" \
  -H "Authorization: Bearer $SKILLSAFE_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}'

import json, urllib.request

TOKEN = "YOUR_TOKEN"   # from /tokens.html
BASE  = "https://api.skillsafe.ai/v1/app-api"

def call(method, path, payload=None, headers=None):
    data = json.dumps(payload).encode() if payload is not None else None
    req = urllib.request.Request(BASE + path, data=data, method=method)
    req.add_header("Authorization", "Bearer " + TOKEN)
    req.add_header("Content-Type", "application/json")
    req.add_header("Accept", "application/json")
    # A plain urllib request with no User-Agent is refused with 403.
    req.add_header("User-Agent", "video-model-router-client/1.0")
    for k, v in (headers or {}).items():
        req.add_header(k, v)
    with urllib.request.urlopen(req) as r:
        return json.loads(r.read())

payload = {
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}
out = call("POST", "/estimate", payload)
print(out["data"]["hold_credits"], out["data"]["model"])

const TOKEN = "YOUR_TOKEN";   // from /tokens.html
const BASE  = "https://api.skillsafe.ai/v1/app-api";

async function call(method, path, payload) {
  const res = await fetch(BASE + path, {
    method,
    headers: {
      "Authorization": `Bearer ${TOKEN}`,
      "Content-Type": "application/json"
    },
    body: payload === undefined ? undefined : JSON.stringify(payload)
  });
  const json = await res.json();
  if (!res.ok || !json.ok) throw new Error(json.error?.message || res.statusText);
  return json.data;
}

const payload = {
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
};
const data = await call("POST", "/estimate", payload);
console.log(data.hold_credits, data.model, data.model_alias);

package main

import (
	"bytes"
	"fmt"
	"io"
	"net/http"
)

const base = "https://api.skillsafe.ai/v1/app-api"
const token = "YOUR_TOKEN" // from /tokens.html

func main() {
	payload := []byte(`{
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}`)
	req, _ := http.NewRequest("POST", base+"/estimate", bytes.NewReader(payload))
	req.Header.Set("Authorization", "Bearer "+token)
	req.Header.Set("Content-Type", "application/json")
	res, err := http.DefaultClient.Do(req)
	if err != nil {
		panic(err)
	}
	defer res.Body.Close()
	out, _ := io.ReadAll(res.Body)
	fmt.Println(string(out))
}

import java.net.URI;
import java.net.http.*;

public class Main {
    static final String BASE  = "https://api.skillsafe.ai/v1/app-api";
    static final String TOKEN = "YOUR_TOKEN"; // from /tokens.html

    public static void main(String[] args) throws Exception {
        String payload = """
{
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}
""";
        HttpRequest req = HttpRequest.newBuilder()
            .uri(URI.create(BASE + "/estimate"))
            .header("Authorization", "Bearer " + TOKEN)
            .header("Content-Type", "application/json")
            .method("POST", HttpRequest.BodyPublishers.ofString(payload))
            .build();
        HttpResponse<String> res = HttpClient.newHttpClient()
            .send(req, HttpResponse.BodyHandlers.ofString());
        System.out.println(res.body());
    }
}

require 'net/http'
require 'json'
require 'uri'

BASE  = "https://api.skillsafe.ai/v1/app-api"
TOKEN = "YOUR_TOKEN" # from /tokens.html

payload = {
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}

uri = URI("#{BASE}/estimate")
req = Net::HTTP::Post.new(uri)
req["Authorization"] = "Bearer #{TOKEN}"
req["Content-Type"] = "application/json"
req.body = JSON.dump(payload)
res = Net::HTTP.start(uri.hostname, uri.port, use_ssl: true) { |h| h.request(req) }
puts JSON.pretty_generate(JSON.parse(res.body)["data"])

<?php
$base  = "https://api.skillsafe.ai/v1/app-api";
$token = "YOUR_TOKEN"; // from /tokens.html

$payload = json_encode([
  "task" => "veo",
  "shot" => "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets" => "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds" => 12,
  "aspect" => "16:9",
  "resolution" => "1080p",
  "style" => "hyper-realistic luxury commercial, shallow depth of field",
  "audio" => "crystalline chime on the first frame, soft ambient pad, no dialogue"
]);

$opts = ["http" => [
    "method"  => "POST",
    "header"  => "Authorization: Bearer $token\r\nContent-Type: application/json\r\n",
    "content" => $payload,
]];
$res  = file_get_contents($base . "/estimate", false, stream_context_create($opts));
$json = json_decode($res, true);
print_r($json["data"]);

using System.Net.Http;
using System.Text;

const string Base  = "https://api.skillsafe.ai/v1/app-api";
const string Token = "YOUR_TOKEN"; // from /tokens.html

var http = new HttpClient();
http.DefaultRequestHeaders.Add("Authorization", $"Bearer {Token}");

var payload = """
{
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}
""";
var content = new StringContent(payload, Encoding.UTF8, "application/json");
var res = await http.SendAsync(new HttpRequestMessage(new HttpMethod("POST"), Base + "/estimate")
{
    Content = content
});
Console.WriteLine(await res.Content.ReadAsStringAsync());

4. Write a package

POST /run submits the job. Always send an Idempotency-Key: a network blip that replays the same request must not bill twice. A replay with the same key returns the stored result and is not charged again; a replay with the same key but a different body is a 409.

The response carries output.output (the Markdown package), charged_credits and truncated. If truncated is true the balance sat between min_credits and hold_credits and the output was cut short - render what arrived and say so rather than presenting it as complete.

curl -sS -X POST "https://api.skillsafe.ai/v1/app-api/run" \
  -H "Authorization: Bearer $SKILLSAFE_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}'

import json, urllib.request

TOKEN = "YOUR_TOKEN"   # from /tokens.html
BASE  = "https://api.skillsafe.ai/v1/app-api"

def call(method, path, payload=None, headers=None):
    data = json.dumps(payload).encode() if payload is not None else None
    req = urllib.request.Request(BASE + path, data=data, method=method)
    req.add_header("Authorization", "Bearer " + TOKEN)
    req.add_header("Content-Type", "application/json")
    req.add_header("Accept", "application/json")
    # A plain urllib request with no User-Agent is refused with 403.
    req.add_header("User-Agent", "video-model-router-client/1.0")
    for k, v in (headers or {}).items():
        req.add_header(k, v)
    with urllib.request.urlopen(req) as r:
        return json.loads(r.read())

payload = {
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}
out = call("POST", "/run", payload)
print(out["data"]["output"]["output"])

const TOKEN = "YOUR_TOKEN";   // from /tokens.html
const BASE  = "https://api.skillsafe.ai/v1/app-api";

async function call(method, path, payload) {
  const res = await fetch(BASE + path, {
    method,
    headers: {
      "Authorization": `Bearer ${TOKEN}`,
      "Content-Type": "application/json"
    },
    body: payload === undefined ? undefined : JSON.stringify(payload)
  });
  const json = await res.json();
  if (!res.ok || !json.ok) throw new Error(json.error?.message || res.statusText);
  return json.data;
}

const payload = {
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
};
const data = await call("POST", "/run", payload);
console.log(data.output.output);

package main

import (
	"bytes"
	"fmt"
	"io"
	"net/http"
)

const base = "https://api.skillsafe.ai/v1/app-api"
const token = "YOUR_TOKEN" // from /tokens.html

func main() {
	payload := []byte(`{
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}`)
	req, _ := http.NewRequest("POST", base+"/run", bytes.NewReader(payload))
	req.Header.Set("Authorization", "Bearer "+token)
	req.Header.Set("Content-Type", "application/json")
	res, err := http.DefaultClient.Do(req)
	if err != nil {
		panic(err)
	}
	defer res.Body.Close()
	out, _ := io.ReadAll(res.Body)
	fmt.Println(string(out))
}

import java.net.URI;
import java.net.http.*;

public class Main {
    static final String BASE  = "https://api.skillsafe.ai/v1/app-api";
    static final String TOKEN = "YOUR_TOKEN"; // from /tokens.html

    public static void main(String[] args) throws Exception {
        String payload = """
{
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}
""";
        HttpRequest req = HttpRequest.newBuilder()
            .uri(URI.create(BASE + "/run"))
            .header("Authorization", "Bearer " + TOKEN)
            .header("Content-Type", "application/json")
            .method("POST", HttpRequest.BodyPublishers.ofString(payload))
            .build();
        HttpResponse<String> res = HttpClient.newHttpClient()
            .send(req, HttpResponse.BodyHandlers.ofString());
        System.out.println(res.body());
    }
}

require 'net/http'
require 'json'
require 'uri'

BASE  = "https://api.skillsafe.ai/v1/app-api"
TOKEN = "YOUR_TOKEN" # from /tokens.html

payload = {
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}

uri = URI("#{BASE}/run")
req = Net::HTTP::Post.new(uri)
req["Authorization"] = "Bearer #{TOKEN}"
req["Content-Type"] = "application/json"
req.body = JSON.dump(payload)
res = Net::HTTP.start(uri.hostname, uri.port, use_ssl: true) { |h| h.request(req) }
puts JSON.pretty_generate(JSON.parse(res.body)["data"])

<?php
$base  = "https://api.skillsafe.ai/v1/app-api";
$token = "YOUR_TOKEN"; // from /tokens.html

$payload = json_encode([
  "task" => "veo",
  "shot" => "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets" => "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds" => 12,
  "aspect" => "16:9",
  "resolution" => "1080p",
  "style" => "hyper-realistic luxury commercial, shallow depth of field",
  "audio" => "crystalline chime on the first frame, soft ambient pad, no dialogue"
]);

$opts = ["http" => [
    "method"  => "POST",
    "header"  => "Authorization: Bearer $token\r\nContent-Type: application/json\r\n",
    "content" => $payload,
]];
$res  = file_get_contents($base . "/run", false, stream_context_create($opts));
$json = json_decode($res, true);
print_r($json["data"]);

using System.Net.Http;
using System.Text;

const string Base  = "https://api.skillsafe.ai/v1/app-api";
const string Token = "YOUR_TOKEN"; // from /tokens.html

var http = new HttpClient();
http.DefaultRequestHeaders.Add("Authorization", $"Bearer {Token}");

var payload = """
{
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}
""";
var content = new StringContent(payload, Encoding.UTF8, "application/json");
var res = await http.SendAsync(new HttpRequestMessage(new HttpMethod("POST"), Base + "/run")
{
    Content = content
});
Console.WriteLine(await res.Content.ReadAsStringAsync());

5. Stream a run

POST /run-stream is the same call with a text/event-stream response. Worth knowing before you build on it: from a server or from cURL you get event: delta frames carrying the output token by token; from a browser you get event: tick heartbeats and then one event: done with the whole output. Handle both, and treat ticks as liveness rather than progress.

Frame types are job (the job id), delta ({"text": "..."}), tick ({"t": seconds}), done, and error. An idempotent replay returns plain JSON with no stream at all, so check the content type before you start reading frames.

curl -sS -N -X POST "https://api.skillsafe.ai/v1/app-api/run-stream" \
  -H "Authorization: Bearer $SKILLSAFE_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Accept: text/event-stream" \
  -H "Idempotency-Key: vmr-$(date +%s)" \
  -d '{
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}'

import json, urllib.request

TOKEN = "YOUR_TOKEN"
BASE  = "https://api.skillsafe.ai/v1/app-api"

payload = {
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}

req = urllib.request.Request(BASE + "/run-stream", data=json.dumps(payload).encode(), method="POST")
req.add_header("Authorization", "Bearer " + TOKEN)
req.add_header("Content-Type", "application/json")
req.add_header("Accept", "text/event-stream")
req.add_header("Idempotency-Key", "vmr-demo-1")
req.add_header("User-Agent", "video-model-router-client/1.0")

event, data = "message", ""
with urllib.request.urlopen(req) as r:
    for raw in r:
        line = raw.decode().rstrip("\n")
        if line.startswith("event:"):
            event = line[6:].strip()
        elif line.startswith("data:"):
            data += line[5:].strip()
        elif line == "":
            if data:
                frame = json.loads(data)
                if event == "delta":
                    print(frame.get("text", ""), end="")
                elif event == "done":
                    print("\n--- charged:", frame.get("charged_credits"))
            event, data = "message", ""

const TOKEN = "YOUR_TOKEN";
const BASE  = "https://api.skillsafe.ai/v1/app-api";

const payload = {
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
};

const res = await fetch(BASE + "/run-stream", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${TOKEN}`,
    "Content-Type": "application/json",
    "Idempotency-Key": "vmr-demo-1"
  },
  body: JSON.stringify(payload)
});

// An idempotent replay comes back as plain JSON with no stream at all.
if (!(res.headers.get("content-type") || "").includes("text/event-stream")) {
  const json = await res.json();
  console.log(json.data.output.output);
} else {
  const reader = res.body.getReader();
  const dec = new TextDecoder();
  let buf = "";
  for (;;) {
    const { done, value } = await reader.read();
    if (done) break;
    buf += dec.decode(value, { stream: true });
    let i;
    while ((i = buf.indexOf("\n\n")) >= 0) {
      const frame = buf.slice(0, i);
      buf = buf.slice(i + 2);
      let name = "message", data = "";
      for (const line of frame.split("\n")) {
        if (line.startsWith("event:")) name = line.slice(6).trim();
        else if (line.startsWith("data:")) data += line.slice(5).trim();
      }
      if (!data) continue;
      const p = JSON.parse(data);
      if (name === "delta") process.stdout.write(p.text || "");
      if (name === "tick") console.error("still writing:", p.t + "s");
      if (name === "done") console.log("\ncharged:", p.charged_credits);
    }
  }
}

package main

import (
	"bytes"
	"fmt"
	"io"
	"net/http"
)

const base = "https://api.skillsafe.ai/v1/app-api"
const token = "YOUR_TOKEN" // from /tokens.html

func main() {
	payload := []byte(`{
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}`)
	req, _ := http.NewRequest("POST", base+"/run-stream", bytes.NewReader(payload))
	req.Header.Set("Authorization", "Bearer "+token)
	req.Header.Set("Content-Type", "application/json")
	res, err := http.DefaultClient.Do(req)
	if err != nil {
		panic(err)
	}
	defer res.Body.Close()
	out, _ := io.ReadAll(res.Body)
	fmt.Println(string(out))
}

import java.net.URI;
import java.net.http.*;

public class Main {
    static final String BASE  = "https://api.skillsafe.ai/v1/app-api";
    static final String TOKEN = "YOUR_TOKEN"; // from /tokens.html

    public static void main(String[] args) throws Exception {
        String payload = """
{
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}
""";
        HttpRequest req = HttpRequest.newBuilder()
            .uri(URI.create(BASE + "/run-stream"))
            .header("Authorization", "Bearer " + TOKEN)
            .header("Content-Type", "application/json")
            .method("POST", HttpRequest.BodyPublishers.ofString(payload))
            .build();
        HttpResponse<String> res = HttpClient.newHttpClient()
            .send(req, HttpResponse.BodyHandlers.ofString());
        System.out.println(res.body());
    }
}

require 'net/http'
require 'json'
require 'uri'

BASE  = "https://api.skillsafe.ai/v1/app-api"
TOKEN = "YOUR_TOKEN" # from /tokens.html

payload = {
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}

uri = URI("#{BASE}/run-stream")
req = Net::HTTP::Post.new(uri)
req["Authorization"] = "Bearer #{TOKEN}"
req["Content-Type"] = "application/json"
req.body = JSON.dump(payload)
res = Net::HTTP.start(uri.hostname, uri.port, use_ssl: true) { |h| h.request(req) }
puts JSON.pretty_generate(JSON.parse(res.body)["data"])

<?php
$base  = "https://api.skillsafe.ai/v1/app-api";
$token = "YOUR_TOKEN"; // from /tokens.html

$payload = json_encode([
  "task" => "veo",
  "shot" => "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets" => "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds" => 12,
  "aspect" => "16:9",
  "resolution" => "1080p",
  "style" => "hyper-realistic luxury commercial, shallow depth of field",
  "audio" => "crystalline chime on the first frame, soft ambient pad, no dialogue"
]);

$opts = ["http" => [
    "method"  => "POST",
    "header"  => "Authorization: Bearer $token\r\nContent-Type: application/json\r\n",
    "content" => $payload,
]];
$res  = file_get_contents($base . "/run-stream", false, stream_context_create($opts));
$json = json_decode($res, true);
print_r($json["data"]);

using System.Net.Http;
using System.Text;

const string Base  = "https://api.skillsafe.ai/v1/app-api";
const string Token = "YOUR_TOKEN"; // from /tokens.html

var http = new HttpClient();
http.DefaultRequestHeaders.Add("Authorization", $"Bearer {Token}");

var payload = """
{
  "task": "veo",
  "shot": "A frosted glass perfume bottle with a gold cap rotating slowly on a reflective dark surface, like a luxury commercial.",
  "assets": "perfume.png - the product, three-quarter view on white\nmoodboard.jpg - the brand's warm low-key lighting language",
  "seconds": 12,
  "aspect": "16:9",
  "resolution": "1080p",
  "style": "hyper-realistic luxury commercial, shallow depth of field",
  "audio": "crystalline chime on the first frame, soft ambient pad, no dialogue"
}
""";
var content = new StringContent(payload, Encoding.UTF8, "application/json");
var res = await http.SendAsync(new HttpRequestMessage(new HttpMethod("POST"), Base + "/run-stream")
{
    Content = content
});
Console.WriteLine(await res.Content.ReadAsStringAsync());

6. Read the result

output.output is Markdown in the envelope this app's system prompt guarantees: every section is a level-two heading spelled exactly as listed in the lane table above, in that order; tables are GitHub pipe tables with the declared columns; prompts are in fenced blocks opened with three backticks and the word text; checklists are - [x] lines.

So parsing is a split on /^## / - but do it fence-aware, because a prompt block can legitimately contain a line starting with ##. Count the sections you got against the ones the lane declares: a short list means the run was truncated, not that the contract changed.

def sections(md):
    out, name, buf, fence = {}, None, [], False
    for line in md.split("\n"):
        if line.lstrip().startswith("```"):
            fence = not fence
        if not fence and line.startswith("## "):
            if name:
                out[name] = "\n".join(buf).strip()
            name, buf = line[3:].strip(), []
            continue
        if name:
            buf.append(line)
    if name:
        out[name] = "\n".join(buf).strip()
    return out

The artifact most callers want is the fenced text block inside ## Prompt, ## Ported Prompt, ## Motion Prompt or ## Continuation Prompt - that is what you paste into the vendor's console. The fenced json block under ## Config is a ready-made request body.

Rate limits and good manners

/estimate and /me are free. Call them as much as you like, within reason.
A 429 means back off with a delay, not retry immediately.
Send an Idempotency-Key on every /run. Derive it from a hash of the body plus an attempt counter, so a retry of the same request reuses the key and a deliberate re-run gets a new one.
The capability matrix in the web app is client-side only and has no endpoint. The full table - every model's window, audio behaviour, aspect ratios, reference slots and extension support - is published in llms.txt so you can encode the same checks in your own pipeline. The matrix is also sent with every run as prescan, and the system prompt forbids contradicting it.