agent_graph_start
Start a dependency-aware agent graph. Use template=fleet for master architecture/roadmap/testing strategy → OpenCode worker implementation/report → master validation. Master and worker are process roles and may run on the same device through different runners. Pass allowed_devices to choose the Y...
This record as markdown: /tools/io-github-kivanccakmak-yaver/agent-graph-start.md
What agent_graph_start does on Yaver
AI agents invoke agent_graph_start to trigger actions in Yaver. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | — | Optional graph name |
model | string | — | Optional forced model |
nodes | array | — | Optional explicit node list. If omitted, Yaver builds a template graph from prompt/template. Node resource_modes can request self-hosted build, deploy, browser, |
prompt | string | Yes | Goal for the graph. |
runner | string | — | Optional forced runner |
template | string | — | Graph template: fleet (master→OpenCode worker→master validation), full, ship, ask, or audit |
work_dir | string | — | Absolute work directory. Defaults to the current agent work dir. |
master_model | string | — | Optional master model. |
max_parallel | integer | — | Maximum concurrently running nodes |
worker_model | string | — | Optional OpenCode/provider model for worker nodes. |
master_runner | string | — | Runner for fleet planning and final validation. Empty uses the selected master's saved/default runner. |
worker_runner | string | — | Runner for fleet implementation. Defaults to opencode. |
Parameters from the server's own tool schema.
Why agent_graph_start is rated High
Initiates coordinated multi-process agent execution with deployment across mesh devices, affecting system architecture and code generation.
From the tool's definition Start dependency-aware agent graph, process roles, worker implementation, runners, mesh pool.
Risk signalsAccepts raw HTML/template content (template) · High parameter count (44 properties)
Attacks that exploit this kind of access
The rule that runs agent_graph_start safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Yaver, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For agent_graph_start, this is the rule to start with:
agent_graph_start stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Yaver, apply this rule, and every agent_graph_start call is checked against it from then on.
Questions about agent_graph_start
Start a dependency-aware agent graph. Use template=fleet for master architecture/roadmap/testing strategy → OpenCode worker implementation/report → master validation. Master and worker are process roles and may run on the same device through different runners. Pass allowed_devices to choose the Yaver mesh pool. It is categorised as a Execute tool in the Yaver MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
agent_graph_start accepts 12 parameters: name, model, nodes, prompt, runner, template, work_dir, master_model, max_parallel, worker_model, master_runner, worker_runner. Required: prompt. The full parameter table on this page comes from the server's own tool schema.
Register the Yaver MCP server in PolicyLayer and add a rule for agent_graph_start: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Yaver. Nothing to install.
agent_graph_start is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the agent_graph_start rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for agent_graph_start. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
agent_graph_start is provided by the Yaver MCP server (yaver-cli). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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