rig_author
Build + save a multi-node Rig as a GRAPH the runtime executes for real — the agent-side mirror of the human Rig Builder canvas. structure_type: 'dag' (acyclic; parallel + real fan-in) or 'stateful_graph' (cyclic loops + conditional routing). nodes: each {id, skill (a Registry skill name — discove...
This record as markdown: /tools/ai-rokha-rokha/rig-author.md
What rig_author does on Rokha
AI agents invoke rig_author to trigger actions in Rokha. 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 |
|---|---|---|---|
key | string | — | Rig storage key (default 'agent-rig') |
edges | array | — | Directed edges: [{from, to}] node ids |
nodes | array | Yes | Graph nodes: [{id, skill?, label?, instruction?, doc_input?, model?, model_policy?, endpoint?, tool?, params?}] — endpoint/tool/params wire a node to a LIVE MCP |
summary | string | — | Short rig summary |
structure_type | string | — | dag (default) or stateful_graph |
wallet_address | string | — | Owner scope — derived from your auth token over the public MCP door; you don't pass it, and the run door reads the Rig from the same scope. |
Parameters from the server's own tool schema.
Why rig_author is rated High
Executes arbitrary agent workflows with external skills; high blast radius from misconfigured graph logic.
From the tool's definition Build + save multi-node Rig as GRAPH runtime executes for real with skill integration
Attacks that exploit this kind of access
The rule that runs rig_author safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Rokha, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For rig_author, this is the rule to start with:
rig_author 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 Rokha, apply this rule, and every rig_author call is checked against it from then on.
Questions about rig_author
Build + save a multi-node Rig as a GRAPH the runtime executes for real — the agent-side mirror of the human Rig Builder canvas. structure_type: 'dag' (acyclic; parallel + real fan-in) or 'stateful_graph' (cyclic loops + conditional routing). nodes: each {id, skill (a Registry skill name — discover with registry_search), label?, instruction?, doc_input?, model?, model_policy?, endpoint?, tool?, params?, agent?}. agent names a SUB-AGENT persona handle as the step's ACTOR — the step's agentic/instruction execution runs AS that persona (your own agent always; someone else's only while public; a private/missing actor is a typed agent_unavailable step error). endpoint (+ tool + params) wires the node to a LIVE MCP server — the run performs a REAL tools/call there (empty endpoint = the step runs agentically). doc_input: true = a LIGHT LISTING step (the run does a REAL registry lookup + document fetch of the node's skill — no runtime needed). model pins the Anthropic model for the node's agentic execution (e.g. 'claude-sonnet-4-6'); model_policy 'preferred' (default — swap to the best usable model) or 'required' (the step refuses without it, typed model_unavailable; non-Haiku models need the owner's own API key). edges: each {from, to} node id (a dag rejects cycles; a stateful_graph must reach an exit). After authoring it becomes the caller's saved Working Rig, runnable via the run endpoint. It is categorised as a Execute tool in the Rokha MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
rig_author accepts 6 parameters: key, edges, nodes, summary, structure_type, wallet_address. Required: nodes. The full parameter table on this page comes from the server's own tool schema.
Register the Rokha MCP server in PolicyLayer and add a rule for rig_author: 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 Rokha. Nothing to install.
rig_author 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 rig_author 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 rig_author. 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.
rig_author is provided by the Rokha MCP server (https://rokha.ai/mcp/jsonrpc). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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