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task-external-models

Quick-reference for using external AI models in orchestration workflows. External models are invoked via Bash+claudish CLI (deterministic, 100% reliable). Use when confused about how to run external models, "claudish with Bash", "external model in /team", or "how to specify external model". Trigger keywords - "external model", "claudish", "Bash claudish", "external LLM", "model parameter".

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MadAppGang/claude-code
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2026년 2월 12일 12:49
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name
task-external-models
version
2.0.0
description
Quick-reference for using external AI models in orchestration workflows. External models are invoked via Bash+claudish CLI (deterministic, 100% reliable). Use when confused about how to run external models, "claudish with Bash", "external model in /team", or "how to specify external model". Trigger keywords - "external model", "claudish", "Bash claudish", "external LLM", "model parameter".
tags
["external-model","quick-reference","bash","claudish","agent-cli"]
keywords
["external model","grok","gemini","gpt-5","minimax","claudish","bash","external LLM","cli"]
plugin
multimodel
updated
2026-02-11T00:00:00.000Z
# External Models: Quick Reference ## ⚠️ Learn and Reuse Model Preferences Models are learned per context and reused automatically: ```bash cat .claude/multimodel-team.json 2>/dev/null ``` **Flow:** 1. Detect context from task keywords (debug/research/coding/review) 2. If `contextPreferences[context]` has models → **USE THEM** (no asking) 3. If empty (first time for context) → ASK user → SAVE to that context 4. User says "use different models" → ASK and UPDATE **Override triggers:** "use different models", "change models", "update preferences" --- ## The Simple Truth External AI models are invoked via **Bash+claudish CLI**. This is deterministic and 100% reliable. ```bash claudish --model {MODEL_ID} --stdin --quiet < prompt.md > result.md ``` **In /team orchestration:** - **Internal model** (Claude) → `Task(subagent_type: "dev:researcher")` - **External models** (Grok, Gemini, etc.) → `Bash(claudish --model {MODEL_ID} --stdin)` --- ## Bash + claudish Pattern **Works with ANY agent** — deterministic, no LLM compliance needed. ```bash # Pattern claudish --model {MODEL_ID} --stdin --quiet < prompt.md > result.md 2>stderr.log; echo $? > result.exit # Examples claudish --model x-ai/grok-code-fast-1 --stdin --quiet < task.md > grok.md 2>grok-err.log; echo $? > grok.exit claudish --model google/gemini-3-pro-preview --stdin --quiet < task.md > gemini.md 2>gemini-err.log; echo $? > gemini.exit claudish --model openai/gpt-5.2-codex --stdin --quiet < task.md > gpt5.md 2>gpt5-err.log; echo $? > gpt5.exit ``` **CLI Reference:** ``` claudish [options] --model <id> AI model to use (e.g., x-ai/grok-code-fast-1) --stdin Read prompt from stdin --quiet Minimal output ``` **Parallel Execution in /team:** All Bash calls are launched in a SINGLE message with `run_in_background: true`: ```javascript // Internal model via Task Task({ subagent_type: "dev:researcher", description: "Internal Claude vote", run_in_background: true, prompt: "{VOTE_PROMPT}\n\nWrite to: {SESSION_DIR}/internal-result.md" }) // External models via Bash+claudish (all in same message) Bash({ command: "claudish --model x-ai/grok-code-fast-1 --stdin --quiet < {SESSION_DIR}/vote-prompt.md > {SESSION_DIR}/grok-result.md 2>{SESSION_DIR}/grok-stderr.log; echo $? > {SESSION_DIR}/grok.exit", run_in_background: true }) Bash({ command: "claudish --model google/gemini-3-pro-preview --stdin --quiet < {SESSION_DIR}/vote-prompt.md > {SESSION_DIR}/gemini-result.md 2>{SESSION_DIR}/gemini-stderr.log; echo $? > {SESSION_DIR}/gemini.exit", run_in_background: true }) ``` --- ## Common Mistakes | Mistake | Why It Fails | Fix | |---------|--------------|-----| | Missing `--stdin` flag | claudish expects prompt as argument, truncated for large prompts | Use `--stdin` with `< prompt-file.md` | | Not capturing exit code | No way to detect failures | Add `; echo $? > result.exit` | | Not capturing stderr | Error details lost | Add `2>stderr.log` | | `$(cat file.md)` in Task prompt | Shell expansion doesn't work in JSON string parameters | Read file content first, then include in prompt | --- ## Model IDs > **Note:** Model IDs change frequently. Use `claudish --top-models` for current list. ```bash # Get current available models claudish --top-models # Best value paid models claudish --free # Free models # Example model IDs (verify with commands above) x-ai/grok-code-fast-1 # Grok (fast coding) minimax/minimax-m2.5 # MiniMax M2.5 google/gemini-3-pro-preview # Gemini Pro openai/gpt-5.2-codex # GPT-5.2 Codex z-ai/glm-4.7 # GLM 4.7 deepseek/deepseek-v3.2 # DeepSeek v3.2 ``` > **Prefix routing:** Use direct API prefixes for cost savings: `oai/` (OpenAI), `g/` (Gemini), `mmax/` (MiniMax), `kimi/` (Kimi), `glm/` (GLM). --- ## Verifying Models Actually Ran After collecting results from external models, **always verify**: 1. **Check exit code:** `cat {model-slug}.exit` → should be `0` 2. **Check output size:** `wc -c < {model-slug}-result.md` → should be >50 bytes 3. **Check stderr:** `cat {model-slug}-stderr.log` → should be empty or just info 4. **Record in verification table** for /team results display **Verification checklist:** ``` For each external model result: ☐ Exit code is 0 ☐ Result file exists and has >50 bytes ☐ Response contains substantive analysis (not just acknowledgment) ☐ No error messages in stderr log ``` --- ## Related Skills - **multimodel:proxy-mode-reference** - Complete claudish CLI documentation with routing prefixes - **multimodel:multi-model-validation** - Full parallel validation patterns - **multimodel:model-tracking-protocol** - Progress tracking during reviews - **multimodel:error-recovery** - Handle failures and timeouts
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