AgentTeams is a runtime platform where multiple AI agents collaborate in shared Matrix rooms under the coordination of a manager. It is for human-supervised or enterprise workflows that need visible, auditable cooperation among agents running on different runtimes, with shared files and centralized traffic management.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/agentscope-ai/agentteams/worker-model-switchnpx skills add agentscope-ai/AgentTeams --skill worker-model-switchgit clone --depth 1 https://github.com/agentscope-ai/AgentTeamsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/agentscope-ai/agentteams/worker-model-switch)<a href="https://agentmods.dev/skills/agentscope-ai/agentteams/worker-model-switch"><img src="https://agentmods.dev/badge/skills/agentscope-ai/agentteams/worker-model-switch.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00029 | $0.00355 |
| Opus 5 | $0.00015 | $0.00178 |
| Sonnet 5 | $0.00006 | $0.00071 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
worker-model-switch scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Worker Model Switch
Switch a Worker's LLM model using the agt CLI. The controller handles all details: model parameter resolution, openclaw.json generation, storage push, and container recreation.
Usage
agt update worker --name <WORKER_NAME> --model <MODEL_ID>
Examples:
agt update worker --name alice --model claude-sonnet-4-6
agt update worker --name alice --model deepseek-chat
What happens
The controller automatically:
- Updates the Worker CR's
spec.model - Resolves model parameters (contextWindow, maxTokens, reasoning, input modalities) from its built-in model registry
- Regenerates
openclaw.jsonand pushes it to storage - Recreates the Worker container
You do NOT need to specify context window, reasoning, or any model parameters — the controller knows them.
On success
The CLI prints worker/<name> configured. The controller reconciles the change automatically. No manual restart is needed.
On failure
Report the CLI error output to the human admin. Common causes:
- Worker name does not exist
- Controller API is unreachable
Unknown models
If the admin requests a model not in the controller's built-in registry, the controller uses safe defaults (contextWindow=150000, maxTokens=128000, reasoning=true, input=["text"]). If the admin needs specific parameters for an unknown model, they should update the controller's model registry rather than overriding at the skill level.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 45 lines · 29 tokens per session scan A caa3095605ea
worker-model-switch is a skill published in the GitHub repository agentscope-ai/AgentTeams (5,564 stars, last pushed today), licensed Apache-2.0. It adds 29 tokens to every session and 355 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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