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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".

Quellinformationen

Repository
MadAppGang/claude-code
Letzte Quellaktivität
12. Februar 2026 um 12:49
Erkannte Sprache von SKILL.md
Englisch
Sterne
284
Forks
25

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

SKILL.md wird angezeigt

SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
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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