Intelligent Router — Core Skill

CORE SKILL: This skill is infrastructure, not guidance. Installation = enforcement. Run
bash skills/intelligent-router/install.sh
to activate.

What It Does

Automatically classifies any task into a tier (SIMPLE/MEDIUM/COMPLEX/REASONING/CRITICAL) and recommends the cheapest model that can handle it well.

The problem it solves: Without routing, every cron job and sub-agent defaults to Sonnet (expensive). With routing, monitoring tasks use free local models, saving 80-95% on cost.

MANDATORY Protocol (enforced via AGENTS.md)

Before spawning any sub-agent:

python3 skills/intelligent-router/scripts/router.py classify "task description"

Before creating any cron job:

python3 skills/intelligent-router/scripts/spawn_helper.py "task description"
# Outputs the exact model ID and payload snippet to use

To validate a cron payload has model set:

python3 skills/intelligent-router/scripts/spawn_helper.py --validate '{"kind":"agentTurn","message":"..."}'

❌ VIOLATION (never do this):

# Cron job without model = Sonnet default = expensive waste
{"kind": "agentTurn", "message": "check server..."}  # ← WRONG

✅ CORRECT:

# Always specify model from router recommendation
{"kind": "agentTurn", "message": "check server...", "model": "ollama/glm-4.7-flash"}

Tier System

Tier	Use For	Primary Model	Cost
🟢 SIMPLE	Monitoring, heartbeat, checks, summaries	`anthropic-proxy-6/glm-4.7` (alt: proxy-4)	$0.50/M
🟡 MEDIUM	Code fixes, patches, research, data analysis	`nvidia-nim/meta/llama-3.3-70b-instruct`	$0.40/M
🟠 COMPLEX	Features, architecture, multi-file, debug	`anthropic/claude-sonnet-4-6`	$3/M
🔵 REASONING	Proofs, formal logic, deep analysis	`nvidia-nim/moonshotai/kimi-k2-thinking`	$1/M
🔴 CRITICAL	Security, production, high-stakes	`anthropic/claude-opus-4-6`	$5/M

SIMPLE fallback chain:

anthropic-proxy-4/glm-4.7

→

nvidia-nim/qwen/qwen2.5-7b-instruct

($0.15/M)

⚠️
ollama-gpu-server
is BLOCKED for cron/spawn use. Ollama binds to
127.0.0.1
by default — unreachable over LAN from the OpenClaw host. The
router_policy.py
enforcer will reject any payload referencing it.

Tier classification uses 4 capability signals (not cost alone):

```
effective_params
```
(50%) — extracted from model ID or
```
known-model-params.json
```
for closed-source models
```
context_window
```
(20%) — larger = more capable
```
cost_input
```
(20%) — price as quality proxy (weak signal, last resort for unknown sizes)
```
reasoning_flag
```
(10%) — bonus for dedicated thinking specialists (R1, QwQ, Kimi-K2)

Policy Enforcer (NEW in v3.2.0)

router_policy.py

catches bad model assignments before they are created, not after they fail.

Validate a cron payload before submitting

python3 skills/intelligent-router/scripts/router_policy.py check \
  '{"kind":"agentTurn","model":"ollama-gpu-server/glm-4.7-flash","message":"check server"}'
# Output: VIOLATION: Blocked model 'ollama-gpu-server/glm-4.7-flash'. Recommended: anthropic-proxy-6/glm-4.7

Get enforced model recommendation for a task

python3 skills/intelligent-router/scripts/router_policy.py recommend "monitor alphastrike service"
# Output: Tier: SIMPLE  Model: anthropic-proxy-6/glm-4.7
python3 skills/intelligent-router/scripts/router_policy.py recommend "monitor alphastrike service" --alt
Output: Tier: SIMPLE  Model: anthropic-proxy-4/glm-4.7  ← alternate key for load distribution

Audit all existing cron jobs

python3 skills/intelligent-router/scripts/router_policy.py audit
# Scans all crons, reports any with blocked or missing models

Show blocklist

python3 skills/intelligent-router/scripts/router_policy.py blocklist

Policy rules enforced

Model must be set — no model field = Sonnet default = expensive waste
No blocked models —
```
ollama-gpu-server/*
```
and bare
```
ollama/*
```
are rejected for cron use
CRITICAL tasks — warns if using a non-Opus model for classified-critical work

Installation (Core Skill Setup)

Run once to self-integrate into AGENTS.md:

bash skills/intelligent-router/install.sh

This patches AGENTS.md with the mandatory protocol so it's always in context.

CLI Reference

# ── Policy enforcer (run before creating any cron/spawn) ──
python3 skills/intelligent-router/scripts/router_policy.py check '{"kind":"agentTurn","model":"...","message":"..."}'
python3 skills/intelligent-router/scripts/router_policy.py recommend "task description"
python3 skills/intelligent-router/scripts/router_policy.py recommend "task" --alt  # alternate proxy key
python3 skills/intelligent-router/scripts/router_policy.py audit     # scan all crons
python3 skills/intelligent-router/scripts/router_policy.py blocklist
── Core router ──
Classify + recommend model
python3 skills/intelligent-router/scripts/router.py classify "task"
Get model id only (for scripting)
python3 skills/intelligent-router/scripts/spawn_helper.py --model-only "task"
Show spawn command
python3 skills/intelligent-router/scripts/spawn_helper.py "task"
Validate cron payload has model set
python3 skills/intelligent-router/scripts/spawn_helper.py --validate '{"kind":"agentTurn","message":"..."}'
List all models by tier
python3 skills/intelligent-router/scripts/router.py models
Detailed scoring breakdown
python3 skills/intelligent-router/scripts/router.py score "task"
Config health check
python3 skills/intelligent-router/scripts/router.py health
Auto-discover working models (NEW)
python3 skills/intelligent-router/scripts/discover_models.py
Auto-discover + update config
python3 skills/intelligent-router/scripts/discover_models.py --auto-update
Test specific tier only

python3 skills/intelligent-router/scripts/discover_models.py --tier COMPLEX

Scoring System

15-dimension weighted scoring (not just keywords):

Reasoning markers (0.18) — prove, theorem, derive
Code presence (0.15) — code blocks, file extensions
Multi-step patterns (0.12) — first...then, numbered lists
Agentic task (0.10) — run, fix, deploy, build
Technical terms (0.10) — architecture, security, protocol
Token count (0.08) — complexity from length
Creative markers (0.05) — story, compose, brainstorm
Question complexity (0.05) — multiple who/what/how
Constraint count (0.04) — must, require, exactly
Imperative verbs (0.03) — analyze, evaluate, audit
Output format (0.03) — json, table, markdown
Simple indicators (0.02) — check, get, show (inverted)
Domain specificity (0.02) — acronyms, dotted notation
Reference complexity (0.02) — "mentioned above"
Negation complexity (0.01) — not, never, except

Confidence:

1 / (1 + exp(-8 × (score - 0.5)))

Config

Models defined in

config.json

. Add new models there, router picks them up automatically. Local Ollama models have zero cost — always prefer them for SIMPLE tasks.

Auto-Discovery (Self-Healing)

The intelligent-router can automatically discover working models from all configured providers via real live inference tests (not config-existence checks).

How It Works

Provider Scanning: Reads
```
~/.openclaw/openclaw.json
```
→ finds all models
Live Inference Test: Sends
```
"hi"
```
to each model, checks it actually responds (catches auth failures, quota exhaustion, 404s, timeouts)
OAuth Bypass: Providers with
```
sk-ant-oat01-*
```
tokens (Anthropic OAuth) are skipped in raw HTTP — OpenClaw refreshes these transparently, so they're always marked available
Thinking Model Support: Models that return
```
content=None
```
+
```
reasoning_content
```
(GLM-4.7, Kimi-K2, Qwen3-thinking) are correctly detected as available
Auto-Classification: Tiers assigned via
```
tier_classifier.py
```
using 4 capability signals
Config Update: Removes unavailable models, rebuilds tier primaries from working set
Cron: Hourly refresh (cron id:
```
a8992c1f
```
) keeps model list current, alerts if availability changes by >2

Usage

# One-time discovery
python3 skills/intelligent-router/scripts/discover_models.py
Auto-update config with working models only
python3 skills/intelligent-router/scripts/discover_models.py --auto-update
Set up hourly refresh cron

openclaw cron add --job '{
"name": "Model Discovery Refresh",
"schedule": {"kind": "every", "everyMs": 3600000},
"payload": {
"kind": "systemEvent",
"text": "Run: bash skills/intelligent-router/scripts/auto_refresh_models.sh",
"model": "ollama/glm-4.7-flash"
}
}'

Benefits

✅ Self-healing: Automatically removes broken models (e.g., expired OAuth) ✅ Zero maintenance: No manual model list updates ✅ New models: Auto-adds newly released models ✅ Cost optimization: Always uses cheapest working model per tier

Discovery Output

Results saved to

skills/intelligent-router/discovered-models.json

{
  "scan_timestamp": "2026-02-19T21:00:00",
  "total_models": 25,
  "available_models": 23,
  "unavailable_models": 2,
  "providers": {
    "anthropic": {
      "available": 2,
      "unavailable": 0,
      "models": [...]
    }
  }
}

Pinning Models

To preserve a model even if it fails discovery:

{
  "id": "special-model",
  "tier": "COMPLEX",
  "pinned": true  // Never remove during auto-update
}

⚠️ Known Gap — Proactive Health-Based Routing (2026-03-04)

Current router is reactive not proactive:

Fallback only fires AFTER a 429 is received
No awareness of concurrent sessions on same proxy
No cooldown tracking after rate-limit events

Needed improvements:

Track last-429 timestamp per provider → skip if within cooldown window
Track active concurrent spawns per provider → if >1 active, route to OAuth
Before spawning N parallel agents, check if single provider can handle N concurrent

Expose

router.get_best_available(n_concurrent=2)

API

Intelligent Model Router

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Intelligent Router — Core Skill

What It Does

MANDATORY Protocol (enforced via AGENTS.md)

Before spawning any sub-agent:

Before creating any cron job:

To validate a cron payload has model set:

❌ VIOLATION (never do this):

✅ CORRECT:

Tier System

Policy Enforcer (NEW in v3.2.0)

Validate a cron payload before submitting

Get enforced model recommendation for a task

Output: Tier: SIMPLE Model: anthropic-proxy-4/glm-4.7 ← alternate key for load distribution

Audit all existing cron jobs

Show blocklist

Policy rules enforced

Installation (Core Skill Setup)

CLI Reference

── Core router ──

Classify + recommend model

Get model id only (for scripting)

Show spawn command

Validate cron payload has model set

List all models by tier

Detailed scoring breakdown

Config health check

Auto-discover working models (NEW)

Auto-discover + update config

Test specific tier only

Scoring System

Config

Auto-Discovery (Self-Healing)

How It Works

Usage

Auto-update config with working models only

Set up hourly refresh cron

Benefits

Discovery Output

Pinning Models

⚠️ Known Gap — Proactive Health-Based Routing (2026-03-04)

Quick Start

Manual Installation

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