proxy-mode-reference
Reference guide for using external AI models via claudish CLI. Use when running multi-model reviews, understanding how /team invokes external models, or debugging external model integration issues. Includes routing prefixes for MiniMax, Kimi, GLM direct APIs.
Best use case
proxy-mode-reference is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Reference guide for using external AI models via claudish CLI. Use when running multi-model reviews, understanding how /team invokes external models, or debugging external model integration issues. Includes routing prefixes for MiniMax, Kimi, GLM direct APIs.
Teams using proxy-mode-reference should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/proxy-mode-reference/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How proxy-mode-reference Compares
| Feature / Agent | proxy-mode-reference | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Reference guide for using external AI models via claudish CLI. Use when running multi-model reviews, understanding how /team invokes external models, or debugging external model integration issues. Includes routing prefixes for MiniMax, Kimi, GLM direct APIs.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# External Models via Claudish CLI — Reference Guide
## ⚠️ Learn and Reuse Model Preferences
Models are learned per context and reused automatically:
```bash
cat .claude/multimodel-team.json 2>/dev/null
```
1. Detect context from task keywords (debug/research/coding/review)
2. If `contextPreferences[context]` exists → **USE IT** (no asking)
3. If empty (first time) → ASK user → SAVE for that context
4. User says "change models" → UPDATE preferences
---
## How External Models Work
External models are invoked **deterministically** via the claudish CLI. The orchestrator
(e.g., `/team` command) calls claudish directly through Bash — no LLM delegation needed.
```
Orchestrator → Bash(claudish --model {MODEL_ID} --stdin) → External Model
```
This approach is 100% reliable because it's a direct CLI invocation, not a prompt-based delegation.
## Invoking External Models
### From /team Command (Automatic)
The `/team` command handles this automatically:
- **Internal models** → Task(dev:researcher)
- **External models** → Bash(claudish --model {MODEL_ID} --stdin)
### Direct CLI Usage
```bash
# Pattern
claudish --model {MODEL_ID} --stdin --quiet < prompt-file.md > result.md
# Examples
claudish --model x-ai/grok-code-fast-1 --stdin --quiet < task.md > grok-result.md
claudish --model google/gemini-3-pro-preview --stdin --quiet < task.md > gemini-result.md
```
**Required flags:**
- `--model` — The external model to use
- `--stdin` — Read prompt from stdin (for large prompts)
- `--quiet` — Suppress log messages (for clean output capture)
## Multi-Backend Routing
Claudish routes to different backends based on model ID prefix:
| Prefix | Backend | Required Key | Example |
|--------|---------|--------------|---------|
| (none) | OpenRouter | `OPENROUTER_API_KEY` | `openai/gpt-5.2` |
| `g/` `gemini/` | Google Gemini API | `GEMINI_API_KEY` | `g/gemini-2.0-flash` |
| `oai/` | OpenAI Direct API | `OPENAI_API_KEY` | `oai/gpt-4o` |
| `mmax/` `mm/` | MiniMax Direct API | `MINIMAX_API_KEY` | `mmax/MiniMax-M2.1` |
| `kimi/` `moonshot/` | Kimi Direct API | `KIMI_API_KEY` | `kimi/kimi-k2-thinking-turbo` |
| `glm/` `zhipu/` | GLM Direct API | `GLM_API_KEY` | `glm/glm-4.7` |
| `ollama/` | Ollama (local) | None | `ollama/llama3.2` |
| `lmstudio/` | LM Studio (local) | None | `lmstudio/qwen` |
| `vllm/` | vLLM (local) | None | `vllm/model` |
| `mlx/` | MLX (local) | None | `mlx/model` |
| `http://...` | Custom endpoint | None | `http://localhost:8000/model` |
### ⚠️ Prefix Collision Warning
OpenRouter model IDs may collide with routing prefixes. Check the prefix table above.
**Collision-free models (safe for OpenRouter):**
- `x-ai/grok-*` ✅
- `deepseek/*` ✅
- `minimax/*` ✅ (use `mmax/` for MiniMax Direct)
- `qwen/*` ✅
- `mistralai/*` ✅
- `moonshotai/*` ✅ (use `kimi/` for Kimi Direct)
- `anthropic/*` ✅
- `z-ai/*` ✅ (use `glm/` for GLM Direct)
- `google/*` ✅ (use `g/` for Gemini Direct)
- `openai/*` ✅ (use `oai/` for OpenAI Direct)
**Direct API prefixes for cost savings:**
| OpenRouter Model | Direct API Prefix | Notes |
|------------------|-------------------|-------|
| `openai/gpt-*` | `oai/gpt-*` | OpenAI Direct API |
| `google/gemini-*` | `g/gemini-*` | Gemini Direct API |
| `minimax/*` | `mmax/*` or `mm/*` | MiniMax Direct API |
| `moonshotai/*` | `kimi/*` or `moonshot/` | Kimi Direct API |
| `z-ai/glm-*` | `glm/*` or `zhipu/*` | GLM Direct API |
---
## Correct Usage Patterns
### Single External Model
```bash
claudish --model x-ai/grok-code-fast-1 --stdin --quiet < task.md > result.md
```
### Parallel External Models (in /team)
```bash
# All launched in a single message with run_in_background: true
Bash("claudish --model x-ai/grok-code-fast-1 --stdin --quiet < vote-prompt.md > grok-result.md 2>grok-stderr.log; echo $? > grok.exit")
Bash("claudish --model google/gemini-3-pro-preview --stdin --quiet < vote-prompt.md > gemini-result.md 2>gemini-stderr.log; echo $? > gemini.exit")
```
### Verifying Results
```bash
# Check exit code
cat grok.exit # 0 = success
# Check output size
wc -c < grok-result.md # Should be >50 bytes
# Check stderr for errors
cat grok-stderr.log
```
## Common Mistakes
### Mistake 1: Not capturing exit code
```bash
# ❌ WRONG - no way to detect failures
claudish --model grok --stdin < task.md > result.md
# ✅ CORRECT - capture exit code
claudish --model grok --stdin < task.md > result.md 2>stderr.log; echo $? > result.exit
```
## Troubleshooting
### "claudish: command not found"
**Fix:** `npm install -g claudish`
### "OPENROUTER_API_KEY not set"
**Fix:** `export OPENROUTER_API_KEY=your-key`
### Non-zero exit code
**Fix:** Check stderr log for error details. Common causes: rate limits, invalid model ID, API key issues.Related Skills
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