runtime_state_digest
Capture a compact, stable-ordered JSON snapshot of a live subtree's salient state (read-only) — position, rotation, scale, visibility, and modulate by default, or a caller-supplied field list. Deterministic ordering makes it ideal for frame-by-frame comparison alongside runtime_step_frames.
This record as markdown: /tools/breakpoint-mcp/runtime-state-digest.md
What runtime_state_digest does on Breakpoint
AI agents invoke runtime_state_digest to trigger actions in Breakpoint. 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 |
|---|---|---|---|
peer | string | — | Headless peer id from runtime_spawn_peers; omit for the default running game. |
root | string | Yes | Root node path in the running scene |
fields | array | — | Property names to capture per node (default: position/global_position/rotation/scale/visible/modulate when present) |
max_depth | integer | — | Max recursion depth (default 8) |
Parameters from the server's own tool schema.
Why runtime_state_digest is rated High
runtime_state_digest triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Attacks that exploit this kind of access
The rule that runs runtime_state_digest safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Breakpoint, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For runtime_state_digest, this is the rule to start with:
runtime_state_digest 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 Breakpoint, apply this rule, and every runtime_state_digest call is checked against it from then on.
Questions about runtime_state_digest
Capture a compact, stable-ordered JSON snapshot of a live subtree's salient state (read-only) — position, rotation, scale, visibility, and modulate by default, or a caller-supplied field list. Deterministic ordering makes it ideal for frame-by-frame comparison alongside runtime_step_frames. It is categorised as a Execute tool in the Breakpoint MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
runtime_state_digest accepts 4 parameters: peer, root, fields, max_depth. Required: root. The full parameter table on this page comes from the server's own tool schema.
Register the Breakpoint MCP server in PolicyLayer and add a rule for runtime_state_digest: 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 Breakpoint. Nothing to install.
runtime_state_digest 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 runtime_state_digest 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 runtime_state_digest. 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.
runtime_state_digest is provided by the Breakpoint MCP server (breakpoint-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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