# Send LLM Council Router to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
## Suggested prompts
### New install

```text
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
```
### Upgrade existing

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
```json
{
  "schemaVersion": "1.0",
  "item": {
    "slug": "llmcouncil-router",
    "name": "LLM Council Router",
    "source": "tencent",
    "type": "skill",
    "category": "AI 智能",
    "sourceUrl": "https://clawhub.ai/ashtiwariasu/llmcouncil-router",
    "canonicalUrl": "https://clawhub.ai/ashtiwariasu/llmcouncil-router",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadUrl": "/downloads/llmcouncil-router",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=llmcouncil-router",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "packageFormat": "ZIP package",
    "primaryDoc": "SKILL.md",
    "includedAssets": [
      "SKILL.md"
    ],
    "downloadMode": "redirect",
    "sourceHealth": {
      "source": "tencent",
      "slug": "llmcouncil-router",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-05-02T03:37:30.361Z",
      "expiresAt": "2026-05-09T03:37:30.361Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=llmcouncil-router",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=llmcouncil-router",
        "contentDisposition": "attachment; filename=\"llmcouncil-router-1.0.0.zip\"",
        "redirectLocation": null,
        "bodySnippet": null,
        "slug": "llmcouncil-router"
      },
      "scope": "item",
      "summary": "Item download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this item.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/llmcouncil-router"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    }
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/llmcouncil-router",
    "downloadUrl": "https://openagent3.xyz/downloads/llmcouncil-router",
    "agentUrl": "https://openagent3.xyz/skills/llmcouncil-router/agent",
    "manifestUrl": "https://openagent3.xyz/skills/llmcouncil-router/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/llmcouncil-router/agent.md"
  }
}
```
## Documentation

### LLM Council Router

Route any prompt to the best-performing LLM. The API finds the top model for a given query based on thousands of peer-reviewed council deliberations — then you call that model directly.

### Base URL

https://clawbot.llmcouncil.ai

### Authentication

Use the X-API-Key header with your LLM Council API key.

X-API-Key: clwb_YOUR_KEY_HERE

Get a free key at llmcouncil.ai/developers.

### Endpoint: POST /v1/route

Find the best-performing model for a query.

### Request

{
  "query": "Explain quantum entanglement simply",
  "k": 20
}

FieldTypeRequiredDescriptionquerystringYesThe prompt or question to routekintegerNoNumber of past evaluations to consider (default: 20)

### Response

{
  "query": "Explain quantum entanglement simply",
  "nearest_councils": 20,
  "model": "anthropic/claude-sonnet-4",
  "relevance": 0.8234,
  "confidence": 0.65,
  "model_rankings": [
    { "rank": 1, "model": "anthropic/claude-sonnet-4", "nearby_wins": 13, "nearby_appearances": 20 },
    { "rank": 2, "model": "openai/gpt-4.1", "nearby_wins": 5, "nearby_appearances": 18 }
  ]
}

FieldTypeDescriptionmodelstringTop recommended model ID (matches OpenRouter catalogue)relevancefloat (0–1)How closely matched evaluations relate to your query. Above 0.75 is strong.confidencefloat (0–1)How decisively the top model outperforms alternatives. Higher = clearer winner.nearest_councilsintegerNumber of relevant past evaluations usedmodel_rankingsarrayAll models ranked by performance across matched evaluations

### How to use this skill

When the user asks you to find the best model for a task, or when you need to decide which LLM to use:

Call the routing API with the user's query:

curl -X POST https://clawbot.llmcouncil.ai/v1/route \\
  -H "Content-Type: application/json" \\
  -H "X-API-Key: $LLMCOUNCIL_API_KEY" \\
  -d '{"query": "USER_QUERY_HERE"}'

Read the response — the model field is the best-performing model for that query type.


Chain with OpenRouter — model IDs match the OpenRouter catalogue directly, no mapping needed:

import requests, os

# Step 1: Get the best model from LLM Council
route = requests.post(
    "https://clawbot.llmcouncil.ai/v1/route",
    headers={"X-API-Key": os.environ["LLMCOUNCIL_API_KEY"]},
    json={"query": "Write a Python web scraper"},
).json()

best_model = route["model"]       # e.g. "anthropic/claude-sonnet-4"
confidence = route["confidence"]   # e.g. 0.85

# Step 2: Call that model via OpenRouter
answer = requests.post(
    "https://openrouter.ai/api/v1/chat/completions",
    headers={"Authorization": f"Bearer {os.environ['OPENROUTER_API_KEY']}"},
    json={
        "model": best_model,
        "messages": [{"role": "user", "content": "Write a Python web scraper"}],
    },
).json()

print(answer["choices"][0]["message"]["content"])

### Rate Limits

TierDaily LimitAttributionFree100 requests/dayRequiredPro10,000 requests/dayNone

### When to use this

User asks "which model is best for X?"
You need to pick the optimal model for a specific task type
You want data-driven model selection instead of guessing
You want to chain model routing with OpenRouter for automatic best-model dispatch
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: ashtiwariasu
- Version: 1.0.0
## Source health
- Status: healthy
- Item download looks usable.
- Yavira can redirect you to the upstream package for this item.
- Health scope: item
- Reason: direct_download_ok
- Checked at: 2026-05-02T03:37:30.361Z
- Expires at: 2026-05-09T03:37:30.361Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/llmcouncil-router)
- [Send to Agent page](https://openagent3.xyz/skills/llmcouncil-router/agent)
- [JSON manifest](https://openagent3.xyz/skills/llmcouncil-router/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/llmcouncil-router/agent.md)
- [Download page](https://openagent3.xyz/downloads/llmcouncil-router)