artifacts_refresh
Re-render a data-driven artifact from a small data payload and publish a new version at the SAME URL. The artifact must have been created/updated with a template (HTML containing {{placeholder}} tokens). Pass data as a flat map of placeholder -> value (e.g. {"leads": "3 200", "date": "15 июля 202...
This record as markdown: /tools/io-github-saloprj-dialogbrain/artifacts-refresh.md
What artifacts_refresh does on Dialogbrain
AI agents use artifacts_refresh to create or update resources in Dialogbrain, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Dialogbrain environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
data | object | Yes | Flat map of {{placeholder}} name -> value. Every placeholder in the template must be present. Values are HTML-escaped. |
label | string | — | Optional version label (e.g. 'daily refresh'). |
artifact_id | integer | Yes | The data-driven artifact to refresh. |
Parameters from the server's own tool schema.
Why artifacts_refresh is rated Medium
This tool modifies existing data (artifact content) by re-rendering and publishing a new version at an existing URL. This is reversible modification typical of Write operations. It does not delete data (not Destructive), does not execute arbitrary code (not Execute), and has no financial implications (not Financial).
From the tool's definition Re-render a data-driven artifact from a small data payload and publish a new version at the SAME URL; substitutes placeholder values into a stored template and publishes the result, modifying existing artifact content.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs artifacts_refresh safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Dialogbrain, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For artifacts_refresh, this is the rule to start with:
artifacts_refresh 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 Dialogbrain, apply this rule, and every artifacts_refresh call is checked against it from then on.
Questions about artifacts_refresh
Re-render a data-driven artifact from a small data payload and publish a new version at the SAME URL. The artifact must have been created/updated with a template (HTML containing {{placeholder}} tokens). Pass data as a flat map of placeholder -> value (e.g. {"leads": "3 200", "date": "15 июля 2026"}); the server substitutes them into the stored template — you do NOT send any HTML. Ideal for scheduled refreshes of live numbers. Every template placeholder must have a value in data, or the call fails. It is categorised as a Write tool in the Dialogbrain MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
artifacts_refresh accepts 3 parameters: data, label, artifact_id. Required: data, artifact_id. The full parameter table on this page comes from the server's own tool schema.
Register the Dialogbrain MCP server in PolicyLayer and add a rule for artifacts_refresh: 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 Dialogbrain. Nothing to install.
artifacts_refresh 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 artifacts_refresh 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 artifacts_refresh. 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.
artifacts_refresh is provided by the Dialogbrain MCP server (https://api.dialogbrain.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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