delegate-to-ai
Route tasks to external AI models via Bifrost and PAL MCP multi-model tools
What this skill does
# Delegate to External AI Routes tasks to specialized models based on task type using Bifrost (single-model) or PAL MCP (multi-model). ## When to Delegate Delegate when Claude is not the best tool: - **Large context** (1M+ tokens) -> cloud large-context tier via Bifrost (auto-routed) - **Math/reasoning** -> a reasoning-capable model via Bifrost (auto-routed) - **Private/offline** -> Local MLX via Bifrost (port 30080 routes to local MLX server) - **Code review consensus** -> Multi-model via PAL `consensus` - **Parallel multi-model research** -> PAL `clink` (when you need multiple model perspectives simultaneously) - **Architecture planning** -> Claude Opus native subagent (Plan mode or `Plan` subagent type) ## Route Selection Local models are named by **capability role**, not physical id. Roles resolve to the resident model via the ai-stack registry (`~/.config/ai-stack/registry.json`, written by nix-ai); never hardcode a physical model id here — when the resident model changes, only the registry changes. Cloud tiers are capability classes; PAL/Bifrost auto-routes each to a current model. | Task Type | Cloud tier | Local role | Route | | --- | --- | --- | --- | | Research (single) | large-context | `large-context` | Bifrost | | Research (multi) | multiple | `large-context`¹ | PAL clink | | Complex Coding | Claude Opus | `coding` | native subagent | | Fast Tasks | Claude Sonnet | `quickest` | Bifrost | | Code Review | multi-model | `most-capable` | PAL consensus | | Architecture | Claude Opus | `most-capable` | native subagent | **Bifrost endpoint**: `http://localhost:30080/v1/chat/completions` (OpenAI-compatible) ¹ In local-only mode, `PAL clink` (multi-model) falls back to the single resident local model (every role resolves to it). ## PAL MCP Tools (multi-model only) - **`clink`** - Parallel queries across multiple models - **`consensus`** - Multi-model agreement for critical decisions All other PAL tools have native Claude Code equivalents — use Bifrost or native subagents instead. ## Workflow 1. **Identify task type** (research, coding, review, architecture) 2. **Select route**: Bifrost for single-model, PAL for multi-model, native subagent for implementation work 3. **Execute**: Bifrost via `curl`/Bash; PAL via MCP tool call; native subagent via Agent tool 4. **Synthesize results** if using multi-model tools ## Local-Only Mode When `localOnlyMode` is enabled or `--local` flag is passed, route all tasks through Bifrost to the local MLX inference server (overrides native subagent rows). No cloud API calls are made. ## Related Skills - auto-maintain (ai-delegation)
Related in AI Agents
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