--- name: alltoken-call description: Six slash-style AllToken commands — /alltoken-chat, /alltoken-image, /alltoken-video, /alltoken-search, /alltoken-models, /alltoken-cost — recognized in chat and run via stdlib Python recipes. Pair with alltoken for full project bootstrap. metadata: version: 1.0.0 homepage: https://alltoken.ai docs: https://alltoken.ai/docs/apis/overview license: MIT openclaw: compat: ">=0.18" companion_skill: ../alltoken/SKILL.md --- # /alltoken-call — direct AllToken commands This skill teaches the host agent to recognize **six slash-style invocations** in user prompts and run the corresponding recipe against the user's AllToken API key. Each command is a self-contained Python 3 stdlib script — no external SDK install required. ## When to invoke this skill (vs `alltoken`) | User wants… | Use | |---|---| | "Generate an image of X" / "Translate this with Claude" / "Show available models" | This skill (`alltoken-call`) | | "Build me an AllToken agent" / "Scaffold a chat app" / "Add AllToken to my project" | `alltoken` instead | | Both | Load both — they don't conflict | ## Prerequisites - `ALLTOKEN_API_KEY` exported in the environment the agent shells out to - `python3` ≥ 3.10 available on `PATH` - Internet access from the agent's host > The agent should refuse to invoke any command in this skill if `ALLTOKEN_API_KEY` is unset, and prompt the user to set it first. ## Trigger recognition Match these patterns **case-insensitively** anywhere in the user's message (a leading `/` is canonical but not required): | Trigger | Command | |---|---| | `/alltoken-chat`, `alltoken chat`, "ask alltoken with model X" | [Command 1](#1-alltoken-chat) | | `/alltoken-image`, `alltoken image`, "generate an image via alltoken", "draw with alltoken" | [Command 2](#2-alltoken-image) | | `/alltoken-video`, `alltoken video`, "make a video on alltoken" | [Command 3](#3-alltoken-video) | | `/alltoken-search`, `alltoken search`, "use alltoken web search", "find with alltoken" | [Command 4](#4-alltoken-search) | | `/alltoken-models`, `alltoken models`, "what alltoken models are available" | [Command 5](#5-alltoken-models) | | `/alltoken-cost`, `alltoken cost`, "how much did that cost" (when last response was an AllToken call) | [Command 6](#6-alltoken-cost) | ## Production constraints baked into the recipes These were verified live on 2026-05-12 — they're not optional: 1. **Image results are one-shot.** Persist `b64_json` on the first `completed` read; re-polling returns `410 image_already_retrieved`. 2. **`enable_search: true` only works on DeepSeek and Qwen.** OpenAI returns 503, Claude/GLM/Kimi/Minimax silently drop it. The `/alltoken-search` recipe defaults to `deepseek-v4-pro` for this reason. 3. **Streaming `usage` requires opt-in.** Add `stream_options: {"include_usage": True}` or it'll be null. 4. **The API key reaches `/v1/*` only.** `/api-account/user/balance`, `/usage`, `/billing` return 401 with the Bearer token — they need a web session. Do not attempt them. 5. **Errors are envelope-shaped:** `{"error": {"code": "", "type": "", "message": "...", "param": null, "request_id": "..."}}`. Always surface `code` and `request_id` to the user on failure. --- ## 1. `/alltoken-chat` **Syntax** ``` /alltoken-chat /alltoken-chat # uses default: gpt-5.4-mini ``` **Parameters** - `model` (optional) — any ID from `/v1/models`. Common choices: `gpt-5.4-mini`, `gpt-5.4`, `claude-sonnet-4-6`, `claude-opus-4-7`, `deepseek-v4-pro`, `gemini-3.1-pro-preview`. Cheap defaults: `gpt-5.4-nano`, `claude-haiku-4-5`, `gemini-3-flash-preview`. - `prompt` (required) — free-form text. **Recipe** — save as `/tmp/at_chat.py`, run with `python3 /tmp/at_chat.py `: ```python import os, sys, json, urllib.request args = sys.argv[1:] if not args: print("usage: at_chat.py [model] "); sys.exit(2) # Heuristic: first arg is model only if it has no spaces AND looks like an ID first = args[0] if len(args) >= 2 and "-" in first and " " not in first and "." in first or first.startswith(("gpt-","claude-","gemini-","deepseek-","glm-","qwen","kimi-","minimax-")): model, prompt = first, " ".join(args[1:]) else: model, prompt = "gpt-5.4-mini", " ".join(args) body = json.dumps({ "model": model, "messages": [{"role":"user","content": prompt}], "stream": True, "stream_options": {"include_usage": True}, }).encode() req = urllib.request.Request("https://api.alltoken.ai/v1/chat/completions", data=body, method="POST", headers={"Authorization": f"Bearer {os.environ['ALLTOKEN_API_KEY']}", "Content-Type":"application/json"}) try: r = urllib.request.urlopen(req, timeout=120) except urllib.error.HTTPError as e: err = json.loads(e.read()).get("error", {}) print(f"\n[error {e.code}] {err.get('code')}/{err.get('type')}: {err.get('message')} req={err.get('request_id')}") sys.exit(1) usage = None for raw in iter(r.readline, b""): line = raw.decode("utf-8","replace").rstrip("\n") if not line or line.startswith(":"): continue if line.startswith("data: "): data = line[6:] if data == "[DONE]": break obj = json.loads(data) if obj.get("usage"): usage = obj["usage"] for ch in obj.get("choices", []): c = ch.get("delta", {}).get("content") if c: sys.stdout.write(c); sys.stdout.flush() print() if usage: print(f"\n[usage] prompt={usage['prompt_tokens']} completion={usage['completion_tokens']} total={usage['total_tokens']} model={model}") ``` **Agent presentation** — after running, show the streamed text to the user and, in a separate line, surface the token usage (`prompt + completion = total`). If the user follows up with `/alltoken-cost`, that line is what gets multiplied by per-token prices. --- ## 2. `/alltoken-image` **Syntax** ``` /alltoken-image [--size=1024x1024] [--quality=low|medium|high] [--out=PATH] ``` **Parameters** - `prompt` (required) - `--size` — `1024x1024` (default), `1536x1024`, `1024x1536`, `auto` - `--quality` — `low` (default for speed), `medium`, `high`, `auto` - `--out` — output path (default: `./alltoken-image-<8charhex>.png` in `cwd`) **Recipe** — save as `/tmp/at_image.py`: ```python import os, sys, json, time, base64, uuid, argparse, urllib.request ap = argparse.ArgumentParser() ap.add_argument("prompt", nargs="+") ap.add_argument("--size", default="1024x1024") ap.add_argument("--quality", default="low", choices=["low","medium","high","auto"]) ap.add_argument("--out", default=None) a = ap.parse_args() prompt = " ".join(a.prompt) out = a.out or f"alltoken-image-{uuid.uuid4().hex[:8]}.png" H = {"Authorization": f"Bearer {os.environ['ALLTOKEN_API_KEY']}", "Content-Type":"application/json"} body = json.dumps({"model":"gpt-image-2","prompt":prompt,"size":a.size,"quality":a.quality}).encode() req = urllib.request.Request("https://api.alltoken.ai/v1/images/generations/async", data=body, method="POST", headers={**H, "Idempotency-Key": str(uuid.uuid4())}) try: created = json.loads(urllib.request.urlopen(req, timeout=60).read()) except urllib.error.HTTPError as e: print(f"[error] submit failed: {e.code} {e.read().decode()[:300]}"); sys.exit(1) task_id = created["id"]; t0 = time.time() print(f"submitted {task_id} (size={a.size} quality={a.quality})", flush=True) while True: time.sleep(2) req = urllib.request.Request(f"https://api.alltoken.ai/v1/images/generations/{task_id}", headers=H) s = json.loads(urllib.request.urlopen(req, timeout=30).read()) print(f" [{time.time()-t0:.0f}s] {s['status']}", flush=True) if s["status"] == "completed": # ONE-SHOT: write immediately, never re-poll with open(out, "wb") as f: f.write(base64.b64decode(s["data"][0]["b64_json"])) print(f"saved {out} ({os.path.getsize(out)} bytes) in {time.time()-t0:.1f}s") u = s.get("usage", {}); print(f"[usage] input={u.get('input_tokens')} output={u.get('output_tokens')} total={u.get('total_tokens')}") break if s["status"] in ("failed","cancelled"): print(f"[error] task ended: {s.get('error')}"); sys.exit(1) ``` **Agent presentation** — confirm the file path, embed/preview the image if the host supports it, and warn the user that the result is gone from the server after retrieval. If the user asks for a variation, run a *new* `/alltoken-image` rather than re-polling the old task. --- ## 3. `/alltoken-video` **Syntax** ``` /alltoken-video [--model=seedance-1.5-pro] [--duration=5] [--ratio=16:9] [--resolution=480p|720p|1080p] ``` **Parameters** - `prompt` (required) - `--model` — `seedance-1.5-pro` (default), `seedance-2.0`, `happyhorse-1.0-t2v`, `happyhorse-1.0-i2v`. Check `/v1/videos/models` for the full list. - `--duration` — seconds, default `5` - `--ratio` — `16:9` (default), `9:16`, `4:3`, `3:4`, `21:9`, `1:1`, `adaptive` - `--resolution` — `480p` (default), `720p`, `1080p` **Recipe** — save as `/tmp/at_video.py`: ```python import os, sys, json, time, argparse, urllib.request ap = argparse.ArgumentParser() ap.add_argument("prompt", nargs="+") ap.add_argument("--model", default="seedance-1.5-pro") ap.add_argument("--duration", type=int, default=5) ap.add_argument("--ratio", default="16:9") ap.add_argument("--resolution", default="480p", choices=["480p","720p","1080p"]) a = ap.parse_args() H = {"Authorization": f"Bearer {os.environ['ALLTOKEN_API_KEY']}", "Content-Type":"application/json"} body = json.dumps({"model":a.model,"prompt":" ".join(a.prompt),"duration":a.duration,"ratio":a.ratio,"resolution":a.resolution}).encode() req = urllib.request.Request("https://api.alltoken.ai/v1/videos/generations", data=body, method="POST", headers=H) try: created = json.loads(urllib.request.urlopen(req, timeout=60).read()) except urllib.error.HTTPError as e: print(f"[error] {e.code} {e.read().decode()[:300]}"); sys.exit(1) vid = created["id"]; t0 = time.time() print(f"submitted {vid}", flush=True) while True: time.sleep(3) req = urllib.request.Request(f"https://api.alltoken.ai/v1/videos/generations/{vid}", headers=H) s = json.loads(urllib.request.urlopen(req, timeout=30).read()) print(f" [{time.time()-t0:.0f}s] {s['status']}", flush=True) if s["status"] == "completed": url = s.get("video_url") ttl = s.get("video_url_ttl", "?") print(f"video_url ({ttl}s TTL): {url}") print(f"resolution={s.get('resolution')} ratio={s.get('ratio')} fps={s.get('fps')}") break if s["status"] in ("failed","cancelled","expired"): print(f"[error] task ended: {s.get('error')}"); sys.exit(1) ``` **Agent presentation** — give the `video_url` (presigned, expires in `video_url_ttl` seconds) and remind the user to download promptly. If they want to cancel mid-generation, `POST /v1/videos/generations/{id}/cancel`. --- ## 4. `/alltoken-search` **Syntax** ``` /alltoken-search /alltoken-search --model=qwen3.6-flash ``` **Parameters** - `query` (required) — natural-language question - `--model` — defaults to `deepseek-v4-pro`. Only DeepSeek and Qwen models honor `enable_search:true`; choose one of: `deepseek-v4-pro`, `deepseek-v3.2`, `qwen3.6-flash`, `qwen3.6-max-preview`. If you pass any other model the recipe will refuse and tell the user why. **Recipe** — save as `/tmp/at_search.py`: ```python import os, sys, json, argparse, urllib.request SEARCH_OK = {"deepseek-v4-pro","deepseek-v3.2","qwen3.6-flash","qwen3.6-max-preview","qwen3.6-plus","qwen3.6-27b"} ap = argparse.ArgumentParser() ap.add_argument("query", nargs="+") ap.add_argument("--model", default="deepseek-v4-pro") a = ap.parse_args() if a.model not in SEARCH_OK: print(f"[refuse] {a.model} does NOT honor enable_search on AllToken today.") print(f" Use one of: {', '.join(sorted(SEARCH_OK))}") sys.exit(2) body = json.dumps({ "model": a.model, "messages": [{"role":"user","content":" ".join(a.query)}], "enable_search": True, "max_tokens": 600, }).encode() req = urllib.request.Request("https://api.alltoken.ai/v1/chat/completions", data=body, method="POST", headers={"Authorization": f"Bearer {os.environ['ALLTOKEN_API_KEY']}", "Content-Type":"application/json"}) try: r = urllib.request.urlopen(req, timeout=120) except urllib.error.HTTPError as e: err = json.loads(e.read()).get("error", {}) print(f"[error {e.code}] {err.get('code')}/{err.get('type')}: {err.get('message')} req={err.get('request_id')}"); sys.exit(1) j = json.loads(r.read()) m = j["choices"][0]["message"] print(m.get("content","").strip()) u = j.get("usage", {}) print(f"\n[usage] prompt={u.get('prompt_tokens')} completion={u.get('completion_tokens')} total={u.get('total_tokens')} model={a.model}") ``` **Agent presentation** — the response should look like a search-grounded answer (current dates, specific numbers). If the model says "I don't have web search" anyway, the family is honoring the flag but the underlying provider failed — re-run with a different model. --- ## 5. `/alltoken-models` **Syntax** ``` /alltoken-models /alltoken-models --type=chat # chat (default), image, video /alltoken-models --filter=claude # substring filter on ID ``` **Recipe** — save as `/tmp/at_models.py`: ```python import os, sys, json, argparse, urllib.request ap = argparse.ArgumentParser() ap.add_argument("--type", default="chat", choices=["chat","image","video"]) ap.add_argument("--filter", default="") a = ap.parse_args() path = {"chat":"/v1/models","image":"/v1/images/models","video":"/v1/videos/models"}[a.type] req = urllib.request.Request(f"https://api.alltoken.ai{path}", headers={"Authorization": f"Bearer {os.environ['ALLTOKEN_API_KEY']}"}) j = json.loads(urllib.request.urlopen(req, timeout=30).read()) ids = [m["id"] for m in j["data"]] if a.filter: ids = [i for i in ids if a.filter.lower() in i.lower()] print(f"{a.type}: {len(ids)} model(s)" + (f" matching '{a.filter}'" if a.filter else "")) for i in ids: print(f" {i}") ``` **Agent presentation** — list IDs in a code block. If the user asks "which is cheapest / fastest / best for code", cross-reference the verified-working table in `alltoken/SKILL.md` `## Discovering models`. --- ## 6. `/alltoken-cost` Compute the cost of a chat call from its `usage` block + per-million prices from the catalog. Useful right after `/alltoken-chat` or `/alltoken-search`. **Syntax** ``` /alltoken-cost ``` **Recipe** — save as `/tmp/at_cost.py`: ```python import os, sys, json, urllib.request if len(sys.argv) != 4: print("usage: at_cost.py "); sys.exit(2) model, pt, ct = sys.argv[1], int(sys.argv[2]), int(sys.argv[3]) # Public catalog — no auth required req = urllib.request.Request(f"https://api.alltoken.ai/api-account/models/{model}") try: j = json.loads(urllib.request.urlopen(req, timeout=30).read()) except urllib.error.HTTPError as e: print(f"[error] catalog lookup failed: {e.code}"); sys.exit(1) # Pricing fields vary; try common keys data = j.get("data", j) p_in = float(data.get("input_price") or data.get("prompt_price") or 0) p_out = float(data.get("output_price") or data.get("completion_price") or 0) # Convention: prices are per 1M tokens cost = (pt / 1_000_000) * p_in + (ct / 1_000_000) * p_out print(f"model: {model}") print(f"prompt tokens: {pt:>10,}") print(f"completion tokens:{ct:>10,}") print(f"input $/1M: ${p_in:.4f}") print(f"output $/1M: ${p_out:.4f}") print(f"───") print(f"total cost: ${cost:.6f}") ``` **Agent presentation** — surface the total in $ to 6 decimal places; for streaming chat, prefer reading the exact figure from the after-`[DONE]` SSE comment line (which is the authoritative per-request cost from AllToken's gateway). Use this recipe as a fallback when that comment line wasn't captured. > Tip: pricing fields in the catalog response have evolved — if `input_price`/`output_price` aren't populated, fall back to inspecting `data` keys: `curl https://api.alltoken.ai/api-account/models/ | jq 'keys'`. --- ## Error handling (shared across all commands) When any recipe hits a non-2xx response, the AllToken envelope is `{"error": {"code", "type", "message", "param", "request_id"}}`. The agent should: 1. Show the user `code` and `message`. 2. Include `request_id` in any support communication. 3. For specific slugs, take action without prompting: - `invalid_api_key` (401): tell the user the key is bad; do not retry. - `image_already_retrieved` (410): tell the user to re-run; the result is gone. - `all_providers_failed` (503): try a different model from the same family, then a different family. - `rate_limited` / HTTP 429: read `Retry-After` (integer seconds), sleep, retry once. - `insufficient_balance` (402): tell the user to top up in Settings → Billing. ## Companion skill If the user wants to *build* something instead of one-shot calls, hand off to `alltoken`: > "If you want me to scaffold a whole agent project around this, load `skills/alltoken/SKILL.md`." ## Resources - AllToken docs: https://alltoken.ai/docs/apis/overview - Live model list: `GET https://api.alltoken.ai/v1/models` (Bearer auth) - Public catalog: `GET https://api.alltoken.ai/api-account/models` (no auth) - Companion bootstrap skill: [`../alltoken/SKILL.md`](../alltoken/SKILL.md) - Companion usage manual: [`../alltoken/USAGE.md`](../alltoken/USAGE.md)