Nested swiss-knife reference for Xiaomi MiMo provider discovery. Discovery protocol (not a reference) for Xiaomi MiMo (小米MiMo) — an OpenAI-/Anthropic-compatible LLM provider whose single API key unlocks a family of ~9 models behind one chat-completions endpoint. The family spans long-context text reasoning, multimodal-input chat (image / audio / video understanding via standard `messages.content[]`), and a text-to-speech line that returns base64 audio (with built-in voice catalogue, voice-design-from-prompt, and voice-cloning-from-sample variants). Marketing surface lives at https://mimo.xiaomi.com; the developer docs are at https://platform.xiaomimimo.com — and the agent should fetch the live docs rather than trust this manual for anything schema-shaped, because the API surface evolves. This skill teaches the agent (1) which two URLs to start from, (2) how to enumerate the current model lineup, (3) how to source the API key from the user's preset library, (4) how to pick the right base URL for their key (pay
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
A direct command skips the review prompt. Inspect the source before running it.
The command stays on one line. Scroll horizontally to inspect it before copying.
Prefer a local copy? Download the files currently available to SkillsMP.
Showing SKILL.md
SKILL.md
Source instructions · Read-only preview
name
xiaomi-mimo
description
Nested swiss-knife reference for Xiaomi MiMo provider discovery. Discovery protocol (not a reference) for Xiaomi MiMo (小米MiMo) — an OpenAI-/Anthropic-compatible LLM provider whose single API key unlocks a family of ~9 models behind one chat-completions endpoint. The family spans long-context text reasoning, multimodal-input chat (image / audio / video understanding via standard `messages.content[]`), and a text-to-speech line that returns base64 audio (with built-in voice catalogue, voice-design-from-prompt, and voice-cloning-from-sample variants). Marketing surface lives at https://mimo.xiaomi.com; the developer docs are at https://platform.xiaomimimo.com — and the agent should fetch the live docs rather than trust this manual for anything schema-shaped, because the API surface evolves. This skill teaches the agent (1) which two URLs to start from, (2) how to enumerate the current model lineup, (3) how to source the API key from the user's preset library, (4) how to pick the right base URL for their key (pay-as-you-go vs Token Plan; three regional clusters), and (5) what to do if the live docs contradict what the agent expects (file a report via the `lingtai-issue-report` skill). Read when the human asks to use MiMo as their LLM, work with multimodal input, generate speech audio, or debug a MiMo connection. Do NOT use for image / video / music *generation* — that's `minimax-cli`. MiMo ships **no MCP servers**; everything is HTTPS chat-completions.
version
2.0.0
last_changed_at
2026-07-18T00:00:00Z
maintenance
If you find stale or incorrect information here, use the lingtai-issue-report skill to assemble evidence and obtain per-issue human consent before filing an issue. Never include secrets, credentials, tokens, or private paths.
xiaomi-mimo
This is a discovery protocol, not a reference. It teaches you where to look for current MiMo capabilities — it does not mirror them. Anything API-shaped (model IDs, request schemas, voice catalogues, quotas) drifts faster than this manual; fetch the live docs every time.
Where to look
Two URLs and an LLM-friendly bulk dump are all the agent needs to bootstrap full knowledge of the API:
# Quick orientation — what doc pages exist right now?
curl -s https://platform.xiaomimimo.com/llms.txt | head -60
# Full dump — when you need everything in context (much larger)
curl -s https://platform.xiaomimimo.com/llms-full.txt | wc -l
The doc index is structured so you can grep for what you need (e.g. grep -i tts, grep -i pricing, grep -i multimodal). Each entry has a verbatim URL — fetch the specific page once you've located it.
Roughly what's behind a MiMo API key
Enough context for the agent to know what kind of question to ask the docs. Verify model IDs and capability claims against the live docs every time — Xiaomi rotates suffixes and adds new variants regularly.
Three rough families share one https://<host>/v1/chat/completions endpoint:
Text-only chat models — long-context reasoning and tool use. Use for plain LLM work; one is the 1M-context flagship.
Multimodal-input chat models — accept image, audio, AND video as content parts (type: "image_url" | "input_audio" | "video_url") alongside text. Output is text. Use for transcription, image OCR, scene description, audio-visual joint reasoning, etc.
Text-to-speech models — accept text, return base64-encoded audio. Three flavours: a built-in voice catalogue, a voice-design variant where you describe the voice in natural language, and a voice-clone variant where you upload a reference audio sample.
To get the current exact model IDs and per-model capability matrix:
# Inspect the OpenAI-compat spec — lists every model the endpoint accepts
curl -s https://platform.xiaomimimo.com/static/docs/api/chat/openai-api.md | head -200
# Or hit the doc index and follow the API path it advertises
curl -s https://platform.xiaomimimo.com/llms.txt | grep -i 'api/chat'
For the modality you actually need, fetch the dedicated guide. The doc tree currently follows static/docs/usage-guide/<topic>.md — grep usage-guide against llms.txt to find the current path, then curl it.
Sourcing the API key
The TUI stores keys in ~/.lingtai-tui/.env and tells each preset which slot to read via manifest.llm.api_key_env. Slots are per-preset, so a user with both pay-as-you-go and a Token Plan account has two distinct env vars.
Resolution: scan presets, find MiMo ones, read their declared slot. Walk
~/.lingtai-tui/presets/*.json; for each manifest.llm.provider == "mimo", print
its api_key_env slot (default MIMO_API_KEY if empty) and base_url so you can
pick the right account/region. (For a recursive JSONC-safe scan, reuse the sibling
../minimax-cli/SKILL.md §3 scanner with provider == "mimo".)
New user-saved presets: MIMO_<N>_API_KEY (no region suffix; N is a counter).
Built-in / legacy presets: MIMO_API_KEY for back-compat.
Once you've picked the right slot, export it for any direct API call:
SLOT=MIMO_1_API_KEY # whichever slot the preset scan returnedexport MIMO_API_KEY=$(grep -E "^${SLOT}=" ~/.lingtai-tui/.env | cut -d= -f2- | tr -d ' ')
export MIMO_BASE_URL=$(...) # see "Picking the host" below
If multiple MiMo presets exist and you can't infer which the human means, ask — don't guess.
Picking the host
MiMo issues two key formats that pair with different host families. They are not interchangeable — using a tp- key against api.xiaomimimo.com or vice versa returns 401 invalid_key.
Key prefix
Host family
Notes
sk-…
api.xiaomimimo.com (single global host)
Pay-as-you-go, per-token billing
tp-…
token-plan-{cn,sgp,ams}.xiaomimimo.com
Token Plan, three regional clusters
For Token Plan, the user's assigned cluster is shown on their Subscription page (platform.xiaomimimo.com/#/console/plan-manage) — the platform pins each plan to one cluster. Don't guess; ask the user, or read manifest.llm.base_url from the preset.
# Note: bare URL is informational; real endpoint is /v1/chat/completions# Inspect the key prefixcase"$MIMO_API_KEY"in
sk-*) export MIMO_BASE_URL="https://api.xiaomimimo.com" ;;
tp-*) echo"Token Plan — set MIMO_BASE_URL to the regional cluster from the user's preset" ;;
*) echo"unknown prefix — verify with the user" ;;
esac
For the Anthropic-compat surface (Token Plan only), the path is /anthropic instead of /v1. Both cluster types speak both APIs.
Switching models in the active preset
The default preset uses one of the multimodal-input models. To swap:
Run /setup, pick mimo, edit the manifest's llm.model field.
Or clone the preset (cp ~/.lingtai-tui/presets/mimo.json …/mimo-pro.json) and edit model.
Important: if you switch to a text-only model, also remove the vision capability from the manifest — otherwise the kernel's vision tool will fire against a text-only model and 400 on image input.
When the docs contradict this skill, file a report
This skill ages. The live docs are authoritative; if you find a discrepancy — a model that no longer exists, a doc URL that 404s, a request shape that returns a clean error against the documented spec, a new capability MiMo shipped that this skill doesn't mention — invoke the lingtai-issue-report skill to assemble a structured report. Don't silently work around the drift; surfacing it is how this skill stays accurate for the next agent. Specific signals worth reporting:
llms.txt no longer returns the doc index (or moved)
A model ID listed in static/docs/api/chat/openai-api.md returns "model not found"
The cluster URL family in this skill's "Picking the host" table no longer matches the platform's current console
A capability advertised at mimo.xiaomi.com (e.g. a new model variant) is missing from the API surface — or vice versa
Pricing or tier limits in the docs differ from what usage fields actually report
Failure modes
Symptom
Likely cause
Fix
401 invalid_key
Wrong key prefix for the host (sk- vs tp-)
Match per the "Picking the host" table; lingtai-issue-report if the doc no longer matches the real prefixes
404 on chat completions
Token Plan account hitting api.xiaomimimo.com (or vice versa)
Swap MIMO_BASE_URL to the right family
Token Plan latency spikes
Wrong regional cluster
Check the user's Subscription page; switch base_url to the assigned cluster
429 Rate limited
Hit RPM/TPM limit
Live docs — current per-model RPM/TPM caps live in static/docs/pricing.md
Vision tool 400s after model swap
Switched to a text-only model but kept vision capability
Remove vision from manifest, or switch model back to a multimodal-input one
Anything else weird
The skill is stale, the docs moved, or MiMo changed behaviour
Fetch llms.txt, follow the trail; if the trail itself is broken, file via lingtai-issue-report
Found a bug or issue? If you encounter any problems with this skill, load the lingtai-issue-report skill and follow its instructions to report it.
