createya-f67c2b — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited createya-f67c2b (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Createya is an AI-platform that aggregates 20+ image and video generation model families under a single API key + single MCP endpoint. Direct access without VPN, billing in rubles. Free credits on signup.
Currently supported via MCP/REST: image and video. Audio and text models are on the roadmap.
createya.ai, crya_sk_, or https://api.createya.ai/mcpAlways call `createya:list_models` first. Do not assume slugs from memory or from this file. The live catalog reflects what's actually available right now (new models added daily, some removed, prices change). This file's examples are illustrative only — agents that hardcode slugs from memory get 404 model_not_found.
If createya:list_models tool is available — proceed. If not, point user to setup:
# One-line install (Claude Code, Cursor, Codex, opencode all supported)
curl -fsSL https://raw.githubusercontent.com/Createya-ai/createya-mcp/main/install.sh \
| bash -s -- crya_sk_YOUR_KEYGet the key at createya.ai/settings/api-keys (free credits on signup).
createya:list_models()Returns a data: [...] array of families, each with:
{
"id": "nano-banana-pro", // ← pass this to run_model
"object": "model_family",
"name": "Nano Banana", // brand
"version": "Pro", // variant
"output_type": "image", // image | video | audio | text
"status": "public" | "test",
"credits_range": { "min": 18, "max": 152 },
"endpoints": [
{
"id": "nano-banana-pro-t2i",
"mode": "text-to-image",
"credits_per_request": 18, // typical (at defaults)
"credits_min": 36,
"credits_max": 152,
"pricing": {
"axes": [...],
"human_description": "resolution: 1K=18кр, 2K=18кр, 4K=36кр; × num_images (1–4)"
},
"parameters_schema": [...],
"media_inputs": [...]
}
]
}Read `credits_range` to estimate cost before running. credits_per_request is the cost at schema defaults, credits_min / credits_max are the actual range across all axis combinations.
*Read `parameters_schema[].constraints`** for typed cross-axis rules (e.g. "при 4K только 16:9/9:16/4:3/3:4 — не 1:1"). Don't violate them — server will reject or downgrade.
createya:run_model({
model: "nano-banana-pro", // family slug — server picks endpoint by input
input: {
prompt: "кот на луне в стиле Studio Ghibli",
aspect_ratio: "16:9"
}
})Family routing — when you pass family slug, server scores endpoints by input shape:
| Input contains | Picks |
|---|---|
start_image_url + end_image_url | first-last-frame |
video_url / input_video | video-to-* |
image_url / input_images[] | image-to-* or -edit |
Just prompt | text-to-* |
If you want a specific endpoint, pass its full slug (e.g. nano-banana-pro-i2i) — it bypasses scoring.
get_balancecreateya:get_balance() → { object: "balance", credits_balance: 21134 }Warn the user before expensive runs (credits_max close to balance). Link to createya.ai for top-up.
After run_model completes (sync) or get_run_status returns completed:
output.urls[0] (or output.url for single-output models)Don't hardcode slugs from this list — always consult list_models for current names. Use these categories to filter:
| User goal | Look for output_type + filter by name |
|---|---|
| Универсальная картинка | image — наиболее «универсальные» (нет узкоспециализированных модификаторов): обычно nano-banana-*, gpt-image-*, flux-* |
| Фотореализм / лица | image — Flux-семейство, Kling Image, Higgsfield Soul |
| Cinematic / артистично | image — Midjourney, Higgsfield Soul, Recraft |
| Свежие модели xAI / Google | image/video — Grok-Imagine, Imagen, Veo |
| Видео OpenAI | video — Sora |
| Видео Google | video — Veo (несколько версий — выбирай по version и credits_range) |
| Видео Kling | video — Kling-Video (несколько версий) |
| Видео ByteDance | video — Seedance (несколько версий) |
| Bytedance image | image — Seedream |
Always verify exact family slug via list_models — the catalog evolves.
Createya's API returns credits_per_request (typical), credits_min, credits_max per endpoint, plus pricing.axes with per-option breakdown. Use these:
credits_per_request tells you the cost at defaultscredits_max is the worst case (high quality + max size + max num_images)credits_min is the cheapest combo — tell user "set quality=low and size=square_hd for ~X credits"pricing.human_description reads like "resolution: 1K=4кр, 2K=7кр, 4K=11кр; × num_images" — surface this when user asks "сколько стоит?"| Error code | Meaning | Action |
|---|---|---|
| 401 Unauthorized | Invalid key or expired | Re-create at /settings/api-keys, key must start with crya_sk_ |
| 402 Insufficient credits | Out of credits | Direct user to createya.ai for top-up |
| 404 Model not found | Slug typo or model unpublished | Re-call `list_models` — agent must not assume slugs from memory |
| 422 Invalid input | Schema mismatch | Re-check parameters_schema and parameters_schema[*].constraints |
| 429 Rate limit | Concurrency cap | Wait or upgrade plan |
| Async stuck | Job timed out | get_run_status shows error; retry the run |
nano-banana-pro) ≠ endpoint slug (e.g. nano-banana-pro-i2i). Family slug works in run_model and gets auto-routed. Endpoint slug works too — explicit.createya:request_upload_url for presigned PUT, or REST POST /v1/uploads (multipart). Then pass the returned CDN URL as image_url / video_url.isHidden: true are filtered out of MCP response. Don't try to pass them.parameters_schema[*].constraints (cross-axis rules). E.g. "For 4K, aspect_ratio must be in [16:9, 9:16, 4:3, 3:4]" — violating these triggers fallback or rejection.~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.