rig_publish
PUBLISH a rig you saved (rig_author) as a registry listing in ONE call — the server reads the rig, turns its graph into the runnable step skeleton (metadata.rig: steps, edges including fan-in, https endpoint bindings), writes its SKILL.md and publishes it under your account. Without this an outsi...
This record as markdown: /tools/ai-rokha-rokha/rig-publish.md
What rig_publish does on Rokha
AI agents use rig_publish to create or update resources in Rokha, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Rokha environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | — | Listing slug (kebab-case). Defaults to the rig's key. |
tags | array | — | Listing tags (default ['rig']). |
rig_id | string | Yes | UUID of the saved rig (rig_author answers it; rig_search finds it). |
description | string | — | Listing description. Defaults to the rig's intent, then its summary. |
Parameters from the server's own tool schema.
Why rig_publish is rated Medium
Creates registry listing and modifies server state; enables external execution access.
From the tool's definition PUBLISH a rig, writes SKILL.md, publishes under your account.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs rig_publish 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_publish, this is the rule to start with:
rig_publish stays usable, but capped: an agent stuck in a loop can't make hundreds of changes 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_publish call is checked against it from then on.
Questions about rig_publish
PUBLISH a rig you saved (rig_author) as a registry listing in ONE call — the server reads the rig, turns its graph into the runnable step skeleton (metadata.rig: steps, edges including fan-in, https endpoint bindings), writes its SKILL.md and publishes it under your account. Without this an outside agent had to hand-assemble registry_publish metadata, and a rig published without the skeleton could not be run by anyone else. After it: anyone runs it with POST /api/rigs/run {rig: <slug>, input} (no account), or rig_run with provider_id 'rokha' + external_id <slug>. The answer carries fidelity_notes — anything the round trip drops. Requires Authorization: Bearer <JWT>; the rig must be yours. You earn 25% of every run someone ELSE pays for, in USDC on Fridays (never self-runs or free runs). It is categorised as a Write tool in the Rokha MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
rig_publish accepts 4 parameters: name, tags, rig_id, description. Required: rig_id. 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_publish: 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_publish is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the rig_publish 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_publish. 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_publish 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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