Low Risk

studio_get_job_result

Poll the render pipeline for a component. Returns false if still running, the multiview image (8 angles) once complete, or an error if the pipeline failed.

Part of the Tesseract server.

studio_get_job_result is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call studio_get_job_result to retrieve information from Tesseract without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though studio_get_job_result only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "studio_get_job_result": {}
  }
}

See the full Tesseract policy for all 46 tools.

Get this rule live on your own Tesseract server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access studio_get_job_result gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so studio_get_job_result only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the studio_get_job_result tool do? +

Poll the render pipeline for a component. Returns false if still running, the multiview image (8 angles) once complete, or an error if the pipeline failed.. It is categorised as a Read tool in the Tesseract MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on studio_get_job_result? +

Register the Tesseract MCP server in PolicyLayer and add a rule for studio_get_job_result: 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 Tesseract. Nothing to install.

What risk level is studio_get_job_result? +

studio_get_job_result is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit studio_get_job_result? +

Yes. Add a rate_limit block to the studio_get_job_result 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.

How do I block studio_get_job_result completely? +

Set action: deny in the PolicyLayer policy for studio_get_job_result. 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.

What MCP server provides studio_get_job_result? +

studio_get_job_result is provided by the Tesseract MCP server (tesseract-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Tesseract tool call.

Deterministic rules across all 46 Tesseract tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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