Smart Spawn

Pick the best AI model for any task using the Smart Spawn API. No plugin needed — just HTTP requests to ss.deeflect.com/api.

Smart Spawn API

Pick the best AI model for any task. Call the API, get a model recommendation, spawn with it.

No plugin required. Works with any OpenClaw instance or any HTTP client.

Quick Start

1. GET ss.deeflect.com/api/pick?task=<description>&budget=<tier>
2. Use the returned model ID in sessions_spawn

Pick Best Model

GET https://ss.deeflect.com/api/pick?task=build+a+react+dashboard&budget=medium

Response:

{
  "data": {
    "id": "anthropic/claude-opus-4.6",
    "name": "Claude Opus 4.6",
    "score": 86,
    "pricing": { "prompt": 5, "completion": 25 },
    "reason": "Best general model at medium budget ($0-5/M) — score: 86"
  }
}

Then spawn:

sessions_spawn(task="Build a React dashboard with auth", model="anthropic/claude-opus-4.6")

Parameters

Param	Required	Description
task	Yes	Task description or category: coding, reasoning, creative, vision, research, fast-cheap, general
budget	No	low ($0-1/M), medium ($0-5/M, default), high ($2-20/M), any
exclude	No	Comma-separated model IDs to skip
context	No	Tags like vision,long-context for routing boost

Get Multiple Recommendations

GET https://ss.deeflect.com/api/recommend?task=coding&budget=low&count=3

Returns diverse models from different providers. Use for collective/parallel spawning.

Compare Models

GET https://ss.deeflect.com/api/compare?models=anthropic/claude-opus-4.6,openai/gpt-5.2

Side-by-side scores, pricing, capabilities.

Browse All Models

GET https://ss.deeflect.com/api/models?category=coding&sort=score&limit=10

Sort by score, cost, efficiency, or any category name.

Decompose Complex Tasks

POST https://ss.deeflect.com/api/decompose
{"task": "Build and deploy a SaaS app", "budget": "medium"}

Returns sequential steps with optimal model per step.

Swarm (Parallel DAG)

POST https://ss.deeflect.com/api/swarm
{"task": "Research competitors and build pitch deck", "budget": "low"}

Returns a dependency graph of parallel tasks with models assigned.

Usage Pattern

For any task that needs a sub-agent:

1. Decide budget — low for cheap/fast, medium for quality, high for best available
2. Call /api/pick with the task description
3. Use the returned id as the model parameter in sessions_spawn
4. If task is complex — use /api/decompose or /api/swarm to break it into subtasks, spawn each with its recommended model

Error Handling

• API down → skip model selection, use sessions_spawn without a model (falls back to default)
• No model found (404) → widen budget to any and retry
• Rate limited (429) → wait and retry, or fall back to default

API Status

GET https://ss.deeflect.com/api/status

Shows model count, data freshness, source health. Data refreshes every 6 hours from 5 benchmark sources.